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215 relations: Academic Press, Addison-Wesley, Algorithmic information theory, Anomaly (natural sciences), Anomaly detection, Applied science, Approximate entropy, Approximation theory, Arnold tongue, Artificial neural network, Astronomy, Autocorrelation, Autoregressive conditional heteroskedasticity, Autoregressive fractionally integrated moving average, Autoregressive integrated moving average, Autoregressive model, Autoregressive–moving-average model, Brain (journal), Cambridge University Press, Change detection, Chaos theory, Chirp, Chirplet transform, Cluster analysis, Codomain, Coherence (signal processing), Conceptual model, Continuous wavelet transform, Control chart, Control engineering, Correlation and dependence, Correlation dimension, Correlation integral, Covariance, Cramér–von Mises criterion, CRC Press, Cross-correlation, Cross-sectional data, Cross-sectional study, Curve, Curve fitting, CUSUM, Cyclostationary process, Data, Data mining, Decomposition of time series, Dennis Gabor, Detrended fluctuation analysis, Digital filter, Digital signal processing, ..., Discrete time and continuous time, Distributed lag, Domain of a function, Doubly stochastic model, Dow Jones Industrial Average, Dynamic Bayesian network, Dynamic time warping, Earthquake prediction, Econometrics, Edit distance, Electroencephalography, Empirical orthogonal functions, Energy (signal processing), Engineering, English language, Entropy encoding, Ergodic process, Estimation, Estimation theory, EViews, EWMA chart, Extrapolation, Fast Fourier transform, Feature (machine learning), Fitness approximation, Flow (mathematics), Forecasting, Fourier transform, Fractional Fourier transform, Frequency domain, Function (mathematics), Fuzzy logic, GapChart, Gaussian process, Geophysics, Harmonic analysis, Heteroscedasticity, Hidden Markov model, Hjorth parameters, Hurst exponent, Index set, Interpolation, Interrupted time series, James Durbin, Kalman filter, Kolmogorov complexity, Kolmogorov–Smirnov test, Line chart, Linear regression, Linear trend estimation, Lyapunov exponent, Machine learning, Mahalanobis distance, Markov switching multifractal, Mathematical finance, MATLAB, Maurice Priestley, Meteorology, Minitab, Minkowski distance, MIT Press, Mollifier, Moment (mathematics), Monte Carlo method, Moving average, Moving-average model, Multivariate analysis, Natural number, Newey–West estimator, Noise (electronics), Nonlinear autoregressive exogenous model, Nonlinear regression, Nonparametric statistics, Norbert Wiener, Numerical analysis, Oxford University Press, Pandas (software), Panel analysis, Panel data, Parametric statistics, Pattern recognition, Pearson correlation coefficient, Phase synchronization, Polynomial, Polynomial interpolation, Polynomial regression, Prais–Winsten estimation, Prediction, Predictive inference, Princeton University Press, Principal component analysis, Probability distribution, Queueing theory, R (programming language), Random walk, Range (mathematics), Rational function, Rényi entropy, Real number, Recurrence plot, Recurrence quantification analysis, Regression analysis, Rudolf E. Kálmán, S (programming language), Sample entropy, SAS (software), Scaled correlation, Scikit-learn, Seasonal adjustment, Seasonality, Seismology, Sequence, Sequence analysis, Shewhart individuals control chart, Short-time Fourier transform, Sign language, Signal processing, Singular spectrum analysis, Smoothing, Spatial analysis, Spearman's rank correlation coefficient, Special functions, Spectral density, Spectral density estimation, Spectral edge frequency, Spectrum, Speech recognition, Spline interpolation, Springer Science+Business Media, SPSS, SPSS Modeler, Standard deviation, State space, State-space representation, Stationary process, Statistical classification, Statistical inference, Statistical learning theory, Statistics, Stochastic, Stochastic process, Stochastic simulation, Sunspot, Supervised learning, Support vector machine, Telecommunications engineering, The Signal and the Noise, Tide, Time, Time domain, Time reversibility, Time series database, Time–frequency analysis, Time–frequency representation, Total correlation, Uncertainty, Unevenly spaced time series, Unit of observation, Univariate analysis, Vector autoregression, Wavelet, Weather forecasting, Weka (machine learning), Wolfram Language, World War II. Expand index (165 more) »
Academic Press
Academic Press is an academic book publisher.
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Addison-Wesley
Addison-Wesley is a publisher of textbooks and computer literature.
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Algorithmic information theory
Algorithmic information theory is a subfield of information theory and computer science that concerns itself with the relationship between computation and information.
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Anomaly (natural sciences)
In the natural sciences, especially in atmospheric and Earth sciences involving applied statistics, an anomaly is the deviation in a quantity from its expected value, e.g., the difference between a measurement and a mean or a model prediction.
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Anomaly detection
In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset.
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Applied science
Applied science is the application of existing scientific knowledge to practical applications, like technology or inventions.
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Approximate entropy
In statistics, an approximate entropy (ApEn) is a technique used to quantify the amount of regularity and the unpredictability of fluctuations over time-series data.
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Approximation theory
In mathematics, approximation theory is concerned with how functions can best be approximated with simpler functions, and with quantitatively characterizing the errors introduced thereby.
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Arnold tongue
In mathematics, particularly in dynamical systems theory, an Arnold tongue is a phase-locked or mode-locked region in a driven (kicked) weakly-coupled harmonic oscillator.
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Artificial neural network
Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains.
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Astronomy
Astronomy (from ἀστρονομία) is a natural science that studies celestial objects and phenomena.
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Autocorrelation
Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay.
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Autoregressive conditional heteroskedasticity
In econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current error term or innovation as a function of the actual sizes of the previous time periods' error terms; often the variance is related to the squares of the previous innovations.
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Autoregressive fractionally integrated moving average
In statistics, autoregressive fractionally integrated moving average models are time series models that generalize ARIMA (autoregressive integrated moving average) models by allowing non-integer values of the differencing parameter.
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Autoregressive integrated moving average
In statistics and econometrics, and in particular in time series analysis, an autoregressive integrated moving average (ARIMA) model is a generalization of an autoregressive moving average (ARMA) model.
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Autoregressive model
In statistics and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it is used to describe certain time-varying processes in nature, economics, etc.
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Autoregressive–moving-average model
In the statistical analysis of time series, autoregressive–moving-average (ARMA) models provide a parsimonious description of a (weakly) stationary stochastic process in terms of two polynomials, one for the autoregression and the second for the moving average.
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Brain (journal)
Brain is a peer-reviewed scientific journal of neurology, founded in 1878 by John Charles Bucknill, David Ferrier, James Crichton-Browne and John Hughlings Jackson.
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Cambridge University Press
Cambridge University Press (CUP) is the publishing business of the University of Cambridge.
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Change detection
In statistical analysis, change detection or change point detection tries to identify times when the probability distribution of a stochastic process or time series changes.
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Chaos theory
Chaos theory is a branch of mathematics focusing on the behavior of dynamical systems that are highly sensitive to initial conditions.
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Chirp
A chirp is a signal in which the frequency increases (up-chirp) or decreases (down-chirp) with time.
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Chirplet transform
In signal processing, the chirplet transform is an inner product of an input signal with a family of analysis primitives called chirplets.
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Cluster analysis
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters).
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Codomain
In mathematics, the codomain or target set of a function is the set into which all of the output of the function is constrained to fall.
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Coherence (signal processing)
The spectral coherence is a statistic that can be used to examine the relation between two signals or data sets.
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Conceptual model
A conceptual model is a representation of a system, made of the composition of concepts which are used to help people know, understand, or simulate a subject the model represents.
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Continuous wavelet transform
In mathematics, a continuous wavelet transform (CWT) is used to divide a continuous-time function into wavelets.
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Control chart
Control charts, also known as Shewhart charts (after Walter A. Shewhart) or process-behavior charts, are a statistical process control tool used to determine if a manufacturing or business process is in a state of control.
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Control engineering
Control engineering or control systems engineering is an engineering discipline that applies automatic control theory to design systems with desired behaviors in control environments.
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Correlation and dependence
In statistics, dependence or association is any statistical relationship, whether causal or not, between two random variables or bivariate data.
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Correlation dimension
In chaos theory, the correlation dimension (denoted by ν) is a measure of the dimensionality of the space occupied by a set of random points, often referred to as a type of fractal dimension.
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Correlation integral
In chaos theory, the correlation integral is the mean probability that the states at two different times are close: where N is the number of considered states \vec(i), \varepsilon is a threshold distance, || \cdot || a norm (e.g. Euclidean norm) and \Theta(\cdot) the Heaviside step function.
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Covariance
In probability theory and statistics, covariance is a measure of the joint variability of two random variables.
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Cramér–von Mises criterion
In statistics the Cramér–von Mises criterion is a criterion used for judging the goodness of fit of a cumulative distribution function F^* compared to a given empirical distribution function F_n, or for comparing two empirical distributions.
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CRC Press
The CRC Press, LLC is a publishing group based in the United States that specializes in producing technical books.
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Cross-correlation
In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other.
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Cross-sectional data
Cross-sectional data, or a cross section of a study population, in statistics and econometrics is a type of data collected by observing many subjects (such as individuals, firms, countries, or regions) at the same point of time, or without regard to differences in time.
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Cross-sectional study
In medical research and social science, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data.
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Curve
In mathematics, a curve (also called a curved line in older texts) is, generally speaking, an object similar to a line but that need not be straight.
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Curve fitting
Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, possibly subject to constraints.
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CUSUM
In statistical quality control, the CUSUM (or cumulative sum control chart) is a sequential analysis technique developed by E. S. Page of the University of Cambridge.
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Cyclostationary process
A cyclostationary process is a signal having statistical properties that vary cyclically with time.
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Data
Data is a set of values of qualitative or quantitative variables.
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Data mining
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
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Decomposition of time series
The decomposition of time series is a statistical task that deconstructs a time series into several components, each representing one of the underlying categories of patterns.
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Dennis Gabor
Dennis Gabor (Gábor Dénes; 5 June 1900 – 9 February 1979) was a Hungarian-British electrical engineer and physicist, most notable for inventing holography, for which he later received the 1971 Nobel Prize in Physics.
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Detrended fluctuation analysis
In stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical self-affinity of a signal.
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Digital filter
In signal processing, a digital filter is a system that performs mathematical operations on a sampled, discrete-time signal to reduce or enhance certain aspects of that signal.
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Digital signal processing
Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations.
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Discrete time and continuous time
In mathematics and in particular mathematical dynamics, discrete time and continuous time are two alternative frameworks within which to model variables that evolve over time.
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Distributed lag
In statistics and econometrics, a distributed lag model is a model for time series data in which a regression equation is used to predict current values of a dependent variable based on both the current values of an explanatory variable and the lagged (past period) values of this explanatory variable.
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Domain of a function
In mathematics, and more specifically in naive set theory, the domain of definition (or simply the domain) of a function is the set of "input" or argument values for which the function is defined.
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Doubly stochastic model
In statistics, a doubly stochastic model is a type of model that can arise in many contexts, but in particular in modelling time-series and stochastic processes.
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Dow Jones Industrial Average
The Dow Jones Industrial Average (DJIA), or simply the Dow, is a stock market index that shows how 30 large, publicly owned companies based in the United States have traded during a standard trading session in the stock market.
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Dynamic Bayesian network
A Dynamic Bayesian Network (DBN) is a Bayesian network which relates variables to each other over adjacent time steps.
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Dynamic time warping
In time series analysis, dynamic time warping (DTW) is one of the algorithms for measuring similarity between two temporal sequences, which may vary in speed.
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Earthquake prediction
Earthquake prediction is a branch of the science of seismology concerned with the specification of the time, location, and magnitude of future earthquakes within stated limits, and particularly "the determination of parameters for the next strong earthquake to occur in a region.
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Econometrics
Econometrics is the application of statistical methods to economic data and is described as the branch of economics that aims to give empirical content to economic relations.
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Edit distance
In computational linguistics and computer science, edit distance is a way of quantifying how dissimilar two strings (e.g., words) are to one another by counting the minimum number of operations required to transform one string into the other.
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Electroencephalography
Electroencephalography (EEG) is an electrophysiological monitoring method to record electrical activity of the brain.
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Empirical orthogonal functions
In statistics and signal processing, the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined from the data.
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Energy (signal processing)
In signal processing, the energy E_s of a continuous-time signal x(t) is defined as the energy E_s of a discrete-time signal x(n) is defined as.
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Engineering
Engineering is the creative application of science, mathematical methods, and empirical evidence to the innovation, design, construction, operation and maintenance of structures, machines, materials, devices, systems, processes, and organizations.
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English language
English is a West Germanic language that was first spoken in early medieval England and is now a global lingua franca.
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Entropy encoding
In information theory an entropy encoding is a lossless data compression scheme that is independent of the specific characteristics of the medium.
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Ergodic process
In econometrics and signal processing, a stochastic process is said to be ergodic if its statistical properties can be deduced from a single, sufficiently long, random sample of the process.
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Estimation
Estimation (or estimating) is the process of finding an estimate, or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable.
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Estimation theory
Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component.
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EViews
EViews (Econometric Views) is a statistical package for Windows, used mainly for time-series oriented econometric analysis.
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EWMA chart
In statistical quality control, the EWMA chart (or exponentially weighted moving average chart) is a type of control chart used to monitor either variables or attributes-type data using the monitored business or industrial process's entire history of output.
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Extrapolation
In mathematics, extrapolation is the process of estimating, beyond the original observation range, the value of a variable on the basis of its relationship with another variable.
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Fast Fourier transform
A fast Fourier transform (FFT) is an algorithm that samples a signal over a period of time (or space) and divides it into its frequency components.
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Feature (machine learning)
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon being observed.
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Fitness approximation
In function optimization, fitness approximation is a method for decreasing the number of fitness function evaluations to reach a target solution.
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Flow (mathematics)
In mathematics, a flow formalizes the idea of the motion of particles in a fluid.
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Forecasting
Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends.
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Fourier transform
The Fourier transform (FT) decomposes a function of time (a signal) into the frequencies that make it up, in a way similar to how a musical chord can be expressed as the frequencies (or pitches) of its constituent notes.
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Fractional Fourier transform
In mathematics, in the area of harmonic analysis, the fractional Fourier transform (FRFT) is a family of linear transformations generalizing the Fourier transform.
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Frequency domain
In electronics, control systems engineering, and statistics, the frequency domain refers to the analysis of mathematical functions or signals with respect to frequency, rather than time.
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Function (mathematics)
In mathematics, a function was originally the idealization of how a varying quantity depends on another quantity.
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Fuzzy logic
Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1.
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GapChart
In information visualization and computing, GapChart is a chart for displaying time series data by using non overlapped thick curves.
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Gaussian process
In probability theory and statistics, a Gaussian process is a stochastic process (a collection of random variables indexed by time or space), such that every finite collection of those random variables has a multivariate normal distribution, i.e. every finite linear combination of them is normally distributed.
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Geophysics
Geophysics is a subject of natural science concerned with the physical processes and physical properties of the Earth and its surrounding space environment, and the use of quantitative methods for their analysis.
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Harmonic analysis
Harmonic analysis is a branch of mathematics concerned with the representation of functions or signals as the superposition of basic waves, and the study of and generalization of the notions of Fourier series and Fourier transforms (i.e. an extended form of Fourier analysis).
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Heteroscedasticity
In statistics, a collection of random variables is heteroscedastic (or heteroskedastic; from Ancient Greek hetero “different” and skedasis “dispersion”) if there are sub-populations that have different variabilities from others.
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Hidden Markov model
Hidden Markov Model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (i.e. hidden) states.
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Hjorth parameters
Hjorth Parameters are indicators of statistical properties used in signal processing in the time domain introduced by Bo Hjorth in 1970.
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Hurst exponent
The Hurst exponent is used as a measure of long-term memory of time series.
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Index set
In mathematics, an index set is a set whose members label (or index) members of another set.
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Interpolation
In the mathematical field of numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points.
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Interrupted time series
Interrupted time series analysis, sometimes known as quasi-experimental time series analysis, is an approach for the analysis of a single time series of data known or conjectured to be affected by interventions (controlled external influences).
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James Durbin
James Durbin FBA (30 June 1923 – 23 June 2012) was a British statistician and econometrician, known particularly for his work on time series analysis and serial correlation.
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Kalman filter
Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe.
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Kolmogorov complexity
In algorithmic information theory (a subfield of computer science and mathematics), the Kolmogorov complexity of an object, such as a piece of text, is the length of the shortest computer program (in a predetermined programming language) that produces the object as output.
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Kolmogorov–Smirnov test
In statistics, the Kolmogorov–Smirnov test (K–S test or KS test) is a nonparametric test of the equality of continuous, one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test).
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Line chart
A line chart or line graph is a type of chart which displays information as a series of data points called 'markers' connected by straight line segments.
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Linear regression
In statistics, linear regression is a linear approach to modelling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables).
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Linear trend estimation
Trend estimation is a statistical technique to aid interpretation of data.
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Lyapunov exponent
In mathematics the Lyapunov exponent or Lyapunov characteristic exponent of a dynamical system is a quantity that characterizes the rate of separation of infinitesimally close trajectories.
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Machine learning
Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
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Mahalanobis distance
The Mahalanobis distance is a measure of the distance between a point P and a distribution D, introduced by P. C. Mahalanobis in 1936.
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Markov switching multifractal
In financial econometrics, the Markov-switching multifractal (MSM) is a model of asset returns developed by Laurent E. Calvet and Adlai J. Fisher that incorporates stochastic volatility components of heterogeneous durations.
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Mathematical finance
Mathematical finance, also known as quantitative finance, is a field of applied mathematics, concerned with mathematical modeling of financial markets.
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MATLAB
MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and proprietary programming language developed by MathWorks.
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Maurice Priestley
Maurice Bertram Priestley (15 March 1933 – 15 June 2013Tata Subba Rao and Granville Tunnicliffe-Wilson, Obituary: Maurice Priestley 1933–2013, 29 August 2013) was a professor of statistics in the School of Mathematics, University of Manchester.
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Meteorology
Meteorology is a branch of the atmospheric sciences which includes atmospheric chemistry and atmospheric physics, with a major focus on weather forecasting.
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Minitab
Minitab is a statistics package developed at the Pennsylvania State University by researchers Barbara F. Ryan, Thomas A. Ryan, Jr., and Brian L. Joiner in 1972.
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Minkowski distance
The Minkowski distance is a metric in a normed vector space which can be considered as a generalization of both the Euclidean distance and the Manhattan distance.
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MIT Press
The MIT Press is a university press affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts (United States).
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Mollifier
In mathematics, mollifiers (also known as approximations to the identity) are smooth functions with special properties, used for example in distribution theory to create sequences of smooth functions approximating nonsmooth (generalized) functions, via convolution.
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Moment (mathematics)
In mathematics, a moment is a specific quantitative measure, used in both mechanics and statistics, of the shape of a set of points.
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Monte Carlo method
Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results.
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Moving average
In statistics, a moving average (rolling average or running average) is a calculation to analyze data points by creating series of averages of different subsets of the full data set.
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Moving-average model
In time series analysis, the moving-average (MA) model is a common approach for modeling univariate time series.
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Multivariate analysis
Multivariate analysis (MVA) is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical outcome variable at a time.
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Natural number
In mathematics, the natural numbers are those used for counting (as in "there are six coins on the table") and ordering (as in "this is the third largest city in the country").
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Newey–West estimator
A Newey–West estimator is used in statistics and econometrics to provide an estimate of the covariance matrix of the parameters of a regression-type model when this model is applied in situations where the standard assumptions of regression analysis do not apply.
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Noise (electronics)
In electronics, noise is an unwanted disturbance in an electrical signal.
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Nonlinear autoregressive exogenous model
In time series modeling, a nonlinear autoregressive exogenous model (NARX) is a nonlinear autoregressive model which has exogenous inputs.
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Nonlinear regression
In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables.
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Nonparametric statistics
Nonparametric statistics is the branch of statistics that is not based solely on parameterized families of probability distributions (common examples of parameters are the mean and variance).
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Norbert Wiener
Norbert Wiener (November 26, 1894 – March 18, 1964) was an American mathematician and philosopher.
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Numerical analysis
Numerical analysis is the study of algorithms that use numerical approximation (as opposed to general symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics).
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Oxford University Press
Oxford University Press (OUP) is the largest university press in the world, and the second oldest after Cambridge University Press.
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Pandas (software)
In computer programming, pandas is a software library written for the Python programming language for data manipulation and analysis.
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Panel analysis
Panel (data) analysis is a statistical method, widely used in social science, epidemiology, and econometrics to analyze two-dimensional (typically cross sectional and longitudinal) panel data.
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Panel data
In statistics and econometrics, panel data or longitudinal data are multi-dimensional data involving measurements over time.
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Parametric statistics
Parametric statistics is a branch of statistics which assumes that sample data comes from a population that follows a probability distribution based on a fixed set of parameters.
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Pattern recognition
Pattern recognition is a branch of machine learning that focuses on the recognition of patterns and regularities in data, although it is in some cases considered to be nearly synonymous with machine learning.
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Pearson correlation coefficient
In statistics, the Pearson correlation coefficient (PCC, pronounced), also referred to as Pearson's r, the Pearson product-moment correlation coefficient (PPMCC) or the bivariate correlation, is a measure of the linear correlation between two variables X and Y. It has a value between +1 and −1, where 1 is total positive linear correlation, 0 is no linear correlation, and −1 is total negative linear correlation.
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Phase synchronization
Phase synchronization is the process by which two or more cyclic signals tend to oscillate with a repeating sequence of relative phase angles.
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Polynomial
In mathematics, a polynomial is an expression consisting of variables (also called indeterminates) and coefficients, that involves only the operations of addition, subtraction, multiplication, and non-negative integer exponents of variables.
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Polynomial interpolation
In numerical analysis, polynomial interpolation is the interpolation of a given data set by the polynomial of lowest possible degree that passes through the points of the dataset.
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Polynomial regression
In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modelled as an nth degree polynomial in x. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean of y, denoted E(y |x), and has been used to describe nonlinear phenomena such as the growth rate of tissues, the distribution of carbon isotopes in lake sediments, and the progression of disease epidemics.
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Prais–Winsten estimation
In econometrics, Prais–Winsten estimation is a procedure meant to take care of the serial correlation of type AR(1) in a linear model.
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Prediction
A prediction (Latin præ-, "before," and dicere, "to say"), or forecast, is a statement about a future event.
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Predictive inference
Predictive inference is an approach to statistical inference that emphasizes the prediction of future observations based on past observations.
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Princeton University Press
Princeton University Press is an independent publisher with close connections to Princeton University.
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Principal component analysis
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.
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Probability distribution
In probability theory and statistics, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment.
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Queueing theory
Queueing theory is the mathematical study of waiting lines, or queues.
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R (programming language)
R is a programming language and free software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing.
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Random walk
A random walk is a mathematical object, known as a stochastic or random process, that describes a path that consists of a succession of random steps on some mathematical space such as the integers.
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Range (mathematics)
In mathematics, and more specifically in naive set theory, the range of a function refers to either the codomain or the image of the function, depending upon usage.
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Rational function
In mathematics, a rational function is any function which can be defined by a rational fraction, i.e. an algebraic fraction such that both the numerator and the denominator are polynomials.
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Rényi entropy
In information theory, the Rényi entropy generalizes the Hartley entropy, the Shannon entropy, the collision entropy and the min entropy.
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Real number
In mathematics, a real number is a value of a continuous quantity that can represent a distance along a line.
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Recurrence plot
In descriptive statistics and chaos theory, a recurrence plot (RP) is a plot showing, for a given moment in time, the times at which a phase space trajectory visits roughly the same area in the phase space.
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Recurrence quantification analysis
Recurrence quantification analysis (RQA) is a method of nonlinear data analysis (cf. chaos theory) for the investigation of dynamical systems.
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Regression analysis
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables.
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Rudolf E. Kálmán
Rudolf Emil Kálmán (Kálmán Rudolf Emil; May 19, 1930 – July 2, 2016) was a Hungarian-born American electrical engineer, mathematician, and inventor.
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S (programming language)
S is a statistical programming language developed primarily by John Chambers and (in earlier versions) Rick Becker and Allan Wilks of Bell Laboratories.
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Sample entropy
Sample entropy (SampEn) is a modification of approximate entropy (ApEn), used for assessing the complexity of physiological time-series signals, diagnosing diseased states.
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SAS (software)
SAS (previously "Statistical Analysis System") is a software suite developed by SAS Institute for advanced analytics, multivariate analyses, business intelligence, data management, and predictive analytics.
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Scaled correlation
In statistics, scaled correlation is a form of a coefficient of correlation applicable to data that have a temporal component such as time series.
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Scikit-learn
Scikit-learn (formerly scikits.learn) is a free software machine learning library for the Python programming language.
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Seasonal adjustment
Seasonal adjustment is a statistical method for removing the seasonal component of a time series that exhibits a seasonal pattern.
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Seasonality
In time series data, seasonality is the presence of variations that occur at specific regular intervals less than a year, such as weekly, monthly, or quarterly.
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Seismology
Seismology (from Ancient Greek σεισμός (seismós) meaning "earthquake" and -λογία (-logía) meaning "study of") is the scientific study of earthquakes and the propagation of elastic waves through the Earth or through other planet-like bodies.
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Sequence
In mathematics, a sequence is an enumerated collection of objects in which repetitions are allowed.
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Sequence analysis
In bioinformatics, sequence analysis is the process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods to understand its features, function, structure, or evolution.
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Shewhart individuals control chart
In statistical quality control, the individual/moving-range chart is a type of control chart used to monitor variables data from a business or industrial process for which it is impractical to use rational subgroups.
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Short-time Fourier transform
The short-time Fourier transform (STFT), is a Fourier-related transform used to determine the sinusoidal frequency and phase content of local sections of a signal as it changes over time.
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Sign language
Sign languages (also known as signed languages) are languages that use manual communication to convey meaning.
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Signal processing
Signal processing concerns the analysis, synthesis, and modification of signals, which are broadly defined as functions conveying "information about the behavior or attributes of some phenomenon", such as sound, images, and biological measurements.
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Singular spectrum analysis
In time series analysis, singular spectrum analysis (SSA) is a nonparametric spectral estimation method.
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Smoothing
In statistics and image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the data, while leaving out noise or other fine-scale structures/rapid phenomena.
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Spatial analysis
Spatial analysis or spatial statistics includes any of the formal techniques which study entities using their topological, geometric, or geographic properties.
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Spearman's rank correlation coefficient
In statistics, Spearman's rank correlation coefficient or Spearman's rho, named after Charles Spearman and often denoted by the Greek letter \rho (rho) or as r_s, is a nonparametric measure of rank correlation (statistical dependence between the rankings of two variables).
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Special functions
Special functions are particular mathematical functions which have more or less established names and notations due to their importance in mathematical analysis, functional analysis, physics, or other applications.
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Spectral density
The power spectrum S_(f) of a time series x(t) describes the distribution of power into frequency components composing that signal.
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Spectral density estimation
In statistical signal processing, the goal of spectral density estimation (SDE) is to estimate the spectral density (also known as the power spectral density) of a random signal from a sequence of time samples of the signal.
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Spectral edge frequency
The spectral edge frequency or SEF is a measure used in signal processing.
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Spectrum
A spectrum (plural spectra or spectrums) is a condition that is not limited to a specific set of values but can vary, without steps, across a continuum.
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Speech recognition
Speech recognition is the inter-disciplinary sub-field of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers.
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Spline interpolation
In the mathematical field of numerical analysis, Spline interpolation is a form of interpolation where the interpolant is a special type of piecewise polynomial called a spline.
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Springer Science+Business Media
Springer Science+Business Media or Springer, part of Springer Nature since 2015, is a global publishing company that publishes books, e-books and peer-reviewed journals in science, humanities, technical and medical (STM) publishing.
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SPSS
SPSS Statistics is a software package used for interactive, or batched, statistical analysis.
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SPSS Modeler
IBM SPSS Modeler is a data mining and text analytics software application from IBM.
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Standard deviation
In statistics, the standard deviation (SD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values.
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State space
In the theory of discrete dynamical systems, a state space is the set of all possible configurations of a system.
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State-space representation
In control engineering, a state-space representation is a mathematical model of a physical system as a set of input, output and state variables related by first-order differential equations or difference equations.
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Stationary process
In mathematics and statistics, a stationary process (a strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose unconditional joint probability distribution does not change when shifted in time.
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Statistical classification
In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.
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Statistical inference
Statistical inference is the process of using data analysis to deduce properties of an underlying probability distribution.
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Statistical learning theory
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis.
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Statistics
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.
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Stochastic
The word stochastic is an adjective in English that describes something that was randomly determined.
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Stochastic process
--> In probability theory and related fields, a stochastic or random process is a mathematical object usually defined as a collection of random variables.
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Stochastic simulation
A stochastic simulation is a simulation that traces the evolution of variables that can change stochastically (randomly) with certain probabilities.
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Sunspot
Sunspots are temporary phenomena on the Sun's photosphere that appear as spots darker than the surrounding areas.
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Supervised learning
Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.
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Support vector machine
In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.
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Telecommunications engineering
Telecommunications engineering is an engineering discipline centered on electrical and computer engineering which seeks to support and enhance telecommunication systems.
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The Signal and the Noise
The Signal and the Noise: Why Most Predictions Fail – but Some Don't (alternatively stylized as The Signal and the Noise: Why So Many Predictions Fail – but Some Don't) is a 2012 book by Nate Silver detailing the art of using probability and statistics as applied to real-world circumstances.
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Tide
Tides are the rise and fall of sea levels caused by the combined effects of the gravitational forces exerted by the Moon and the Sun and the rotation of Earth.
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Time
Time is the indefinite continued progress of existence and events that occur in apparently irreversible succession from the past through the present to the future.
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Time domain
Time domain is the analysis of mathematical functions, physical signals or time series of economic or environmental data, with respect to time.
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Time reversibility
A mathematical or physical process is time-reversible if the dynamics of the process remain well-defined when the sequence of time-states is reversed.
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Time series database
A time series database (TSDB) is a software system that is optimized for handling time series data, arrays of numbers indexed by time (a datetime or a datetime range).
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Time–frequency analysis
In signal processing, time–frequency analysis comprises those techniques that study a signal in both the time and frequency domains simultaneously, using various time–frequency representations.
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Time–frequency representation
A time–frequency representation (TFR) is a view of a signal (taken to be a function of time) represented over both time and frequency.
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Total correlation
In probability theory and in particular in information theory, total correlation (Watanabe 1960) is one of several generalizations of the mutual information.
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Uncertainty
Uncertainty has been called "an unintelligible expression without a straightforward description".
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Unevenly spaced time series
In statistics, signal processing, and econometrics, an unevenly (or unequally or irregularly) spaced time series is a sequence of observation time and value pairs (tn, Xn) with strictly increasing observation times.
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Unit of observation
In statistics, a unit of observation is the unit described by the data that one analyzes.
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Univariate analysis
Univariate analysis is perhaps the simplest form of statistical analysis.
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Vector autoregression
Vector autoregression (VAR) is a stochastic process model used to capture the linear interdependencies among multiple time series.
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Wavelet
A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases, and then decreases back to zero.
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Weather forecasting
Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given location and time.
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Weka (machine learning)
Waikato Environment for Knowledge Analysis (Weka) is a suite of machine learning software written in Java, developed at the University of Waikato, New Zealand.
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Wolfram Language
The Wolfram Language is a general multi-paradigm programming language developed by Wolfram Research and is the programming language of the mathematical symbolic computation program Mathematica and the Wolfram Programming Cloud.
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World War II
World War II (often abbreviated to WWII or WW2), also known as the Second World War, was a global war that lasted from 1939 to 1945, although conflicts reflecting the ideological clash between what would become the Allied and Axis blocs began earlier.
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References
[1] https://en.wikipedia.org/wiki/Time_series
