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ghyp (version 0.9.3)

Expected value and variance: Expected value and variance-covariance of generalized hyperbolic distributions

Description

The function mean returns the expected value. The function vcov returns the variance in the univariate case and the variance-covariance matrix in the multivariate case.

Usage

## S3 method for class 'ghypbase':
mean(x)
## S3 method for class 'ghypbase':
vcov(object)

Arguments

x, object
An object inheriting from class ghypbase.

Value

  • Either the expected value or the variance.

See Also

ghyp, ghypbase-class, Egig to compute the expected value and the variance of the generalized inverse gaussian distributed mixing variable.

Examples

Run this code
## Univariate: Parametric 
  vg.dist <- VG(lambda=1.10,mu=10,sigma=10,gamma=2)
  mean(vg.dist)
  vcov(vg.dist)
  ## Univariate: Empirical                                                 
  vg.sim <- rghyp(10000,vg.dist)
  mean(vg.sim)
  var(vg.sim)

  ## Multivariate: Parametric 
  vg.dist <- VG(lambda=.10,mu=c(55,33),sigma=diag(c(22,888)),gamma=1:2)
  mean(vg.dist)
  vcov(vg.dist)
  ## Multivariate: Empirical                                                 
  vg.sim <- rghyp(10000,vg.dist)
  colMeans(vg.sim)
  var(vg.sim)

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