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58 relations: Almost everywhere, Beta distribution, Beta function, Bit, Calculus of variations, Cauchy distribution, Change of variables, Chi distribution, Chi-squared distribution, Conditional entropy, Covariance, Digamma function, Edwin Thompson Jaynes, Elementary Principles in Statistical Mechanics, Entropy (information theory), Entropy estimation, Erlang distribution, Estimator, Euler–Mascheroni constant, Exponential distribution, F-distribution, Gamma distribution, Gamma function, Generalized normal distribution, Homeomorphism, If and only if, Independence (probability theory), Information theory, Invariant measure, Jacobian matrix and determinant, Joint entropy, Journal of the Royal Statistical Society, Kullback–Leibler divergence, Laplace distribution, Limiting density of discrete points, Log-normal distribution, Logarithm, Logarithmic scale, Logistic distribution, Maxwell–Boltzmann distribution, Multivariate normal distribution, Mutual information, Nat (unit), Normal distribution, Pareto distribution, Physical Review E, Probability density function, Probability distribution, Quantile function, Quantization (signal processing), ..., Random variable, Rayleigh distribution, Self-information, Student's t-distribution, Support (mathematics), Triangular distribution, Uniform distribution (continuous), Weibull distribution. Expand index (8 more) »
Almost everywhere
In measure theory (a branch of mathematical analysis), a property holds almost everywhere if, in a technical sense, the set for which the property holds takes up nearly all possibilities.
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Beta distribution
In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval parametrized by two positive shape parameters, denoted by α and β, that appear as exponents of the random variable and control the shape of the distribution.
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Beta function
In mathematics, the beta function, also called the Euler integral of the first kind, is a special function defined by for.
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Bit
The bit (a portmanteau of binary digit) is a basic unit of information used in computing and digital communications.
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Calculus of variations
Calculus of variations is a field of mathematical analysis that uses variations, which are small changes in functions and functionals, to find maxima and minima of functionals: mappings from a set of functions to the real numbers.
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Cauchy distribution
The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution.
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Change of variables
In mathematics, a change of variables is a basic technique used to simplify problems in which the original variables are replaced with functions of other variables.
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Chi distribution
No description.
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Chi-squared distribution
No description.
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Conditional entropy
In information theory, the conditional entropy (or equivocation) quantifies the amount of information needed to describe the outcome of a random variable Y given that the value of another random variable X is known.
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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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Digamma function
In mathematics, the digamma function is defined as the logarithmic derivative of the gamma function: It is the first of the polygamma functions.
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Edwin Thompson Jaynes
Edwin Thompson Jaynes (July 5, 1922 – April 30, 1998) was the Wayman Crow Distinguished Professor of Physics at Washington University in St. Louis.
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Elementary Principles in Statistical Mechanics
Elementary Principles in Statistical Mechanics, published in March 1902, is a work of scientific literature by Josiah Willard Gibbs which is considered to be the foundation of modern statistical mechanics.
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Entropy (information theory)
Information entropy is the average rate at which information is produced by a stochastic source of data.
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Entropy estimation
In various science/engineering applications, such as independent component analysis, image analysis, genetic analysis, speech recognition, manifold learning, evaluation of the status of biological systems and time delay estimation it is useful to estimate the differential entropy of a system or process, given some observations.
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Erlang distribution
No description.
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Estimator
In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished.
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Euler–Mascheroni constant
The Euler–Mascheroni constant (also called Euler's constant) is a mathematical constant recurring in analysis and number theory, usually denoted by the lowercase Greek letter gamma.
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Exponential distribution
No description.
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F-distribution
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Gamma distribution
In probability theory and statistics, the gamma distribution is a two-parameter family of continuous probability distributions.
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Gamma function
In mathematics, the gamma function (represented by, the capital Greek alphabet letter gamma) is an extension of the factorial function, with its argument shifted down by 1, to real and complex numbers.
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Generalized normal distribution
The generalized normal distribution or generalized Gaussian distribution (GGD) is either of two families of parametric continuous probability distributions on the real line.
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Homeomorphism
In the mathematical field of topology, a homeomorphism or topological isomorphism or bi continuous function is a continuous function between topological spaces that has a continuous inverse function.
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If and only if
In logic and related fields such as mathematics and philosophy, if and only if (shortened iff) is a biconditional logical connective between statements.
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Independence (probability theory)
In probability theory, two events are independent, statistically independent, or stochastically independent if the occurrence of one does not affect the probability of occurrence of the other.
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Information theory
Information theory studies the quantification, storage, and communication of information.
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Invariant measure
In mathematics, an invariant measure is a measure that is preserved by some function.
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Jacobian matrix and determinant
In vector calculus, the Jacobian matrix is the matrix of all first-order partial derivatives of a vector-valued function.
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Joint entropy
In information theory, joint entropy is a measure of the uncertainty associated with a set of variables.
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Journal of the Royal Statistical Society
The Journal of the Royal Statistical Society is a peer-reviewed scientific journal of statistics.
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Kullback–Leibler divergence
In mathematical statistics, the Kullback–Leibler divergence (also called relative entropy) is a measure of how one probability distribution diverges from a second, expected probability distribution.
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Laplace distribution
In probability theory and statistics, the Laplace distribution is a continuous probability distribution named after Pierre-Simon Laplace.
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Limiting density of discrete points
In information theory, the limiting density of discrete points is an adjustment to the formula of Claude Shannon for differential entropy.
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Log-normal distribution
In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed.
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Logarithm
In mathematics, the logarithm is the inverse function to exponentiation.
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Logarithmic scale
A logarithmic scale is a nonlinear scale used when there is a large range of quantities.
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Logistic distribution
In probability theory and statistics, the logistic distribution is a continuous probability distribution.
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Maxwell–Boltzmann distribution
In physics (in particular in statistical mechanics), the Maxwell–Boltzmann distribution is a particular probability distribution named after James Clerk Maxwell and Ludwig Boltzmann.
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Multivariate normal distribution
In probability theory and statistics, the multivariate normal distribution or multivariate Gaussian distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions.
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Mutual information
In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables.
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Nat (unit)
The natural unit of information (symbol: nat), sometimes also nit or nepit, is a unit of information or entropy, based on natural logarithms and powers of ''e'', rather than the powers of 2 and base 2 logarithms, which define the bit.
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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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Pareto distribution
No description.
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Physical Review E
Physical Review E is a peer-reviewed, scientific journal, published monthly by the American Physical Society.
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Probability density function
In probability theory, a probability density function (PDF), or density of a continuous random variable, is a function, whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample.
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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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Quantile function
In probability and statistics, the quantile function specifies, for a given probability in the probability distribution of a random variable, the value at which the probability of the random variable is less than or equal to the given probability.
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Quantization (signal processing)
Quantization, in mathematics and digital signal processing, is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set.
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Random variable
In probability and statistics, a random variable, random quantity, aleatory variable, or stochastic variable is a variable whose possible values are outcomes of a random phenomenon.
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Rayleigh distribution
No description.
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Self-information
In information theory, self-information or surprisal is the surprise when a random variable is sampled.
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Student's t-distribution
In probability and statistics, Student's t-distribution (or simply the t-distribution) is any member of a family of continuous probability distributions that arises when estimating the mean of a normally distributed population in situations where the sample size is small and population standard deviation is unknown.
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Support (mathematics)
In mathematics, the support of a real-valued function f is the subset of the domain containing those elements which are not mapped to zero.
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Triangular distribution
In probability theory and statistics, the triangular distribution is a continuous probability distribution with lower limit a, upper limit b and mode c, where a \left.\begin f(x) &.
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Uniform distribution (continuous)
In probability theory and statistics, the continuous uniform distribution or rectangular distribution is a family of symmetric probability distributions such that for each member of the family, all intervals of the same length on the distribution's support are equally probable.
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Weibull distribution
No description.
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References
[1] https://en.wikipedia.org/wiki/Differential_entropy
