theory and statistics, the covariance function describes how much two random variables change together (their covariance) with varying spatial or temporal...

In statistics, the Matérn covariance, also called the Matérn kernel, is a covariance function used in spatial statistics, geostatistics, machine learning...

defining the covariance function completely defines the process' behaviour. Importantly the non-negative definiteness of this function enables its spectral...

defined. Subtracting the mean before multiplication yields the auto-covariance function between times t 1 {\displaystyle t_{1}} and t 2 {\displaystyle t_{2}}...

calculating covariance Analysis of covariance Autocovariance Covariance function Covariance matrix Covariance operator Distance covariance, or Brownian...

statistics, given a stochastic process, the autocovariance is a function that gives the covariance of the process with itself at pairs of time points. Autocovariance...

In probability theory and statistics, the mathematical concepts of covariance and correlation are very similar. Both describe the degree to which two random...

and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square...

statistics, sometimes the covariance matrix of a multivariate random variable is not known but has to be estimated. Estimation of covariance matrices then deals...

{\displaystyle \left\{Y_{t}\right\}} , the cross-covariance is a function that gives the covariance of one process with the other at pairs of time points...

linear functional x on the element z. Quite similarly, the covariance function of a function-valued random element (in special cases is called random process...

In statistics, the rational quadratic covariance function is used in spatial statistics, geostatistics, machine learning, image analysis, and other fields...

are jointly wide-sense stationary. Then the cross-covariance function and the cross-correlation function are given as follows. R X Y ⁡ ( τ ) ≜   E ⁡ [ X...

probability theory and statistics, a cross-covariance matrix is a matrix whose element in the i, j position is the covariance between the i-th element of a random...

function will be normally distributed, where the covariance between any two samples is the covariance function (or kernel) of the Gaussian process evaluated...

process. In fact, the orthogonal basis functions used in this representation are determined by the covariance function of the process. One can think that...

Basis Functions were developed thereafter. Some methods are the RBF-FD method, the RBF-QR method and the RBF-PUM method. Matérn covariance function Radial...

imply causation Covariance function Pearson product-moment correlation coefficient Correlation function (astronomy) Correlation function (statistical mechanics)...

Covariance matrix adaptation evolution strategy (CMA-ES) is a particular kind of strategy for numerical optimization. Evolution strategies (ES) are stochastic...

fundamental component of Gaussian processes, where the kernel function operates as a covariance function that defines relationships between inputs. Traditionally...

{\displaystyle t} in [ 0 , T ] {\textstyle [0,T]} , and has the following covariance function: E [ B H ( t ) B H ( s ) ] = 1 2 ( | t | 2 H + | s | 2 H − | t −...

Autocovariance, the covariance of a signal with a time-shifted version of itself Covariance function, a function giving the covariance of a random field...

mean function and C {\displaystyle C} is the covariance function. Popular mean functions are low order polynomials and a popular covariance function is...

cloud computing infrastructures. List of stochastic processes topics Covariance function Deterministic system Dynamics of Markovian particles Entropy rate...

stationary if they are both wide-sense stationary and their cross-covariance function K X Y ( t 1 , t 2 ) = E ⁡ [ ( X t 1 − m X ( t 1 ) ) ( Y t 2 − m Y...

to write this kind of polymorphic function without relying on covariance. The array comparison and shuffling functions can be given the parameterized types...

May 1917 – 6 November 2007) was a Swedish statistician. The Matérn covariance function is named after him. Bertil Matérn was born on 18 May 1917 in Gothenburg...

measure of the relationship between two random variables is the covariance. Covariance is a measure of linear relationship between the random variables...

Counternull Counting process Covariance Covariance and correlation Covariance intersection Covariance matrix Covariance function Covariate Cover's theorem...

multivariate normal distribution, and it relies on a pre-defined covariance function, or kernel, that models how pairs of points relate to each other...