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The generalized variance is a scalar value which generalizes variance for multivariate random variables. It was introduced by Samuel S. Wilks. The generalized...

by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized linear models were formulated by John...

is the generalized variance det ( C ) {\displaystyle \det(C)} , the determinant of the covariance matrix. The generalized variance can be shown to be...

additional variance. Learning algorithms typically have some tunable parameters that control bias and variance; for example, linear and Generalized linear...

In statistics, a generalized estimating equation (GEE) is used to estimate the parameters of a generalized linear model with a possible unmeasured correlation...

problems as testing variance components or ANOVA under unequal variances, exact tests for such problems can be obtained based on generalized p-values. In order...

all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity...

autoregressive moving average (ARMA) model is assumed for the error variance, the model is a generalized autoregressive conditional heteroskedasticity (GARCH) model...

of Σ {\displaystyle {\boldsymbol {\Sigma }}} , also known as the generalized variance. The equation above reduces to that of the univariate normal distribution...

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between...

statistics, the variance function is a smooth function that depicts the variance of a random quantity as a function of its mean. The variance function is...

a given random vector. Intuitively, the covariance matrix generalizes the notion of variance to multiple dimensions. As an example, the variation in a...

mean and common variance. In GLS, the prior is generalized to the case where errors may not be independent and may have differing variances. For given fit...

("The generalized T2-statistic", Section 5.7, pp. 199-201), 7 ("The distribution of the sample covariance matrix and the sample generalized variance", Section...

In statistics, a generalized additive model (GAM) is a generalized linear model in which the linear response variable depends linearly on unknown smooth...

plays as the location parameter under the exponentiated generalized Pareto distribution. The variance of Y {\displaystyle Y} ∼ {\displaystyle \sim } e x G...

In statistics, the variance inflation factor (VIF) is the ratio (quotient) of the variance of a parameter estimate when fitting a full model that includes...

the minimum-variance mean (for large normal samples), which is to say the variance of the median will be ~50% greater than the variance of the mean....

fraction of variance unexplained (FVU), since the second term compares the unexplained variance (variance of the model's errors) with the total variance (of the...

^{(1)}=\mu ^{(2)}=\dots =\mu ^{(m)}.} MANOVA is a generalized form of univariate analysis of variance (ANOVA), although, unlike univariate ANOVA, it uses...