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 measure...

In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation...

function erf ⁡ ( x ) {\textstyle \operatorname {erf} (x)} gives the probability of a random variable, with normal distribution of mean 0 and variance...

^{2})=\operatorname {Tw} _{p}(c\mu ,c^{2-p}\sigma ^{2}).} To define the variance function for exponential dispersion models we make use of the mean value mapping...

In statistics and machine learning, the bias–variance tradeoff describes the relationship between a model's complexity, the accuracy of its predictions...

response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized...

Standard score Information ratio Omega ratio Sampling (statistics) Variance function Everitt, Brian (1998). The Cambridge Dictionary of Statistics. Cambridge...

The Allan variance (AVAR), also known as two-sample variance, is a measure of frequency stability in clocks, oscillators and amplifiers. It is named after...

Cats and a list of Animals, or a function returning Cat and a function returning Animal. Depending on the variance of the type constructor, the subtyping...

the conditional variance function, V a r ( Y ∣ X ) = σ 2 ( μ ) {\displaystyle {\rm {{Var}(Y\mid X)=\sigma ^{2}(\mu )}}} , as a function of the conditional...

Gaussian functions is a Gaussian, and the convolution of two Gaussian functions is also a Gaussian, with variance being the sum of the original variances: c...

NEF, called NEF with quadratic variance function (NEF-QVF) because the variance can be written as a quadratic function of the mean. NEF-QVF are discussed...

econometrics, the conditional variance is also known as the scedastic function or skedastic function. Conditional variances are important parts of autoregressive...

distribution when marginalizing over the variance parameter. Student's t distribution has the probability density function (PDF) given by f ( t ) = Γ ( ν + 1...

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

{Var} [Y]=\sigma ^{2}A''(\theta )=\sigma ^{2}V(\mu )\,\!,} with unit variance function V ( μ ) = A ″ ( ( A ′ ) − 1 ( μ ) ) {\displaystyle V(\mu )=A''((A')^{-1}(\mu...

the square root of the variance, known as the standard error. The MSE either assesses the quality of a predictor (i.e., a function mapping arbitrary inputs...

or probability distribution is the square root of its variance. (For a finite population, variance is the average of the squared deviations from the mean...

(1-\mu )} The accompanying plot of skewness as a function of variance and mean shows that maximum variance (1/4) is coupled with zero skewness and the symmetry...

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...

a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given...

minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than...

cumulative distribution function (CDF) of a real-valued random variable X {\displaystyle X} , or just distribution function of X {\displaystyle X} ,...

model that asymptotically manifests a variance to mean power law will be required express a variance function that comes within the domain of attraction...

matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between...

mean and the variance is specified in the form of a variance function giving the variance as a function of the mean. Generally, this function is allowed...

with variance tending to zero. (However, even in some applications, highly oscillatory functions are used as approximations to the delta function, see...

diverge to infinity even faster than sample variance. If a probability distribution has a density function f ( x ) {\displaystyle f(x)} , then the mean...

distribution function of a continuous probability distribution that is peaked around zero and has a parameter that controls for variance can serve as...

inertia. If the function is a probability distribution, then the first moment is the expected value, the second central moment is the variance, the third standardized...