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48 relations: Akaike information criterion, Apache Spark, Autocorrelation, Autoregressive fractionally integrated moving average, Autoregressive model, Autoregressive–moving-average model, Bayesian information criterion, Box–Jenkins method, Confidence interval, Econometrics, Errors and residuals, EViews, Exponential smoothing, Forecasting, Independent and identically distributed random variables, Julia (programming language), Lag operator, Linear combination, Linear regression, Long-range dependence, Mathematical model, MATLAB, Microsoft, Microsoft Analysis Services, Moving-average model, NCSS (statistical software), Normal distribution, Order of integration, Parameter, Partial autocorrelation function, Python (programming language), R (programming language), Random walk, Root-mean-square deviation, Ruby (programming language), SAP ERP, SAP SE, SAS (software), Scala (programming language), SPSS, Stata, Stationary process, Statistics, Time series, Unit root, White noise, Wolfram Mathematica, X-12-ARIMA.
Akaike information criterion
The Akaike information criterion (AIC) is an estimator of the relative quality of statistical models for a given set of data.
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Apache Spark
Apache Spark is an open-source cluster-computing framework.
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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 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 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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Bayesian information criterion
In statistics, the Bayesian information criterion (BIC) or Schwarz criterion (also SBC, SBIC) is a criterion for model selection among a finite set of models; the model with the lowest BIC is preferred.
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Box–Jenkins method
In time series analysis, the Box–Jenkins method, named after the statisticians George Box and Gwilym Jenkins, applies autoregressive moving average (ARMA) or autoregressive integrated moving average (ARIMA) models to find the best fit of a time-series model to past values of a time series.
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Confidence interval
In statistics, a confidence interval (CI) is a type of interval estimate, computed from the statistics of the observed data, that might contain the true value of an unknown population parameter.
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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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Errors and residuals
In statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "theoretical value".
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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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Exponential smoothing
Exponential smoothing is a rule of thumb technique for smoothing time series data using the exponential window function.
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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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Independent and identically distributed random variables
In probability theory and statistics, a sequence or other collection of random variables is independent and identically distributed (i.i.d. or iid or IID) if each random variable has the same probability distribution as the others and all are mutually independent.
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Julia (programming language)
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science, without the typical need of separate compilation to be fast, while also being effective for general-purpose programming, web use or as a specification language.
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Lag operator
In time series analysis, the lag operator (L) or backshift operator (B) operates on an element of a time series to produce the previous element.
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Linear combination
In mathematics, a linear combination is an expression constructed from a set of terms by multiplying each term by a constant and adding the results (e.g. a linear combination of x and y would be any expression of the form ax + by, where a and b are constants).
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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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Long-range dependence
Long-range dependence (LRD), also called long memory or long-range persistence, is a phenomenon that may arise in the analysis of spatial or time series data.
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Mathematical model
A mathematical model is a description of a system using mathematical concepts and language.
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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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Microsoft
Microsoft Corporation (abbreviated as MS) is an American multinational technology company with headquarters in Redmond, Washington.
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Microsoft Analysis Services
Microsoft SQL Server Analysis Services, SSAS, is an online analytical processing (OLAP) and data mining tool in Microsoft SQL Server.
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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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NCSS (statistical software)
NCSS is a statistics package produced and distributed by NCSS, LLC.
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Normal distribution
In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.
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Order of integration
In statistics, the order of integration, denoted I(d), of a time series is a summary statistic, which reports the minimum number of differences required to obtain a covariance-stationary series.
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Parameter
A parameter (from the Ancient Greek παρά, para: "beside", "subsidiary"; and μέτρον, metron: "measure"), generally, is any characteristic that can help in defining or classifying a particular system (meaning an event, project, object, situation, etc.). That is, a parameter is an element of a system that is useful, or critical, when identifying the system, or when evaluating its performance, status, condition, etc.
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Partial autocorrelation function
In time series analysis, the partial autocorrelation function (PACF) gives the partial correlation of a time series with its own lagged values, controlling for the values of the time series at all shorter lags.
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Python (programming language)
Python is an interpreted high-level programming language for general-purpose programming.
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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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Root-mean-square deviation
The root-mean-square deviation (RMSD) or root-mean-square error (RMSE) (or sometimes root-mean-squared error) is a frequently used measure of the differences between values (sample or population values) predicted by a model or an estimator and the values observed.
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Ruby (programming language)
Ruby is a dynamic, interpreted, reflective, object-oriented, general-purpose programming language.
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SAP ERP
SAP ERP is enterprise resource planning software developed by the German company SAP SE.
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SAP SE
SAP SE (Systeme, Anwendungen und Produkte in der Datenverarbeitung, "Systems, Applications & Products in Data Processing") is a German-based European multinational software corporation that makes enterprise software to manage business operations and customer relations.
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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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Scala (programming language)
Scala is a general-purpose programming language providing support for functional programming and a strong static type system.
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SPSS
SPSS Statistics is a software package used for interactive, or batched, statistical analysis.
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Stata
Stata is a general-purpose statistical software package created in 1985 by StataCorp.
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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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Statistics
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.
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Time series
A time series is a series of data points indexed (or listed or graphed) in time order.
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Unit root
In probability theory and statistics, a unit root is a feature of some stochastic processes (such as random walks) that can cause problems in statistical inference involving time series models.
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White noise
In signal processing, white noise is a random signal having equal intensity at different frequencies, giving it a constant power spectral density.
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Wolfram Mathematica
Wolfram Mathematica (usually termed Mathematica) is a modern technical computing system spanning most areas of technical computing — including neural networks, machine learning, image processing, geometry, data science, visualizations, and others.
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X-12-ARIMA
X-12-ARIMA was the U.S. Census Bureau's software package for seasonal adjustment.
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ARIMA, ARIMA forecasting method, ARIMA model, Autoregressive integrated moving average model, Autoregressive integrated moving-average, Differencing, Integrated (random process).
References
[1] https://en.wikipedia.org/wiki/Autoregressive_integrated_moving_average
