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sn (version 2.1.1)

SUNdistr-class: Class "SUNdistr" and its methods

Description

A class of objects representing Unified Skew-Normal (SUN) distributions.

Arguments

Objects from the class

Objects can be created by a call to the function makeSUNdistr or by a suitable transformation of some object of this class.

Slots

dp:

a list of parameters of length five, as described in SUNdistr-base

name:

a character string with the name of the multivariate variable; it can be an empty string.

compNames:

a vector of character strings with the names of the component variables.

HcompNames

a vector of character strings with the names of the hidden variables.

Methods

show

signature(object = "SUNdistr-class"): ...

plot

signature(x = "SUNdistr-class"): ...

summary

signature(object = "SUNdistr-class"): ...

mean

signature(x = "SUNdistr"): ...

vcov

signature(object = "SUNdistr"): ...

Author

Adelchi Azzalini

Details

See SUNdistr-base for a description of the required structure of dp.

Note that here the methods mean and vcov are not applied to data or to a fitted model, but to a probability distribution, of which they provide the mean (expected) value and the variance-covariance matrix.

The object of this class follow the S4 protocol.

See Also

plot,SUNdistr-method, \(\quad\) summary,SUNdistr-method, \(\quad\) affineTransSUNdistr, marginalSUNdistr

convertSN2SUNdistr to convert a SECdistr object with family "SN" or "ESN" to the equivalent SUNdistr-class object

Examples

Run this code
  xi <- c(1, 0, -1)
  Omega <- matrix(c(2,1,1, 1,3,1, 1,1,4), 3, 3)
  Delta <- matrix(c(0.72,0.20, 0.51,0.42, 0.88, 0.94), 3, 2, byrow=TRUE)
  Gamma <- matrix(c(1, 0.8, 0.8, 1), 2, 2)
  dp3 <- list(xi=xi, Omega=Omega, Delta=Delta, tau=c(-0.5, 0), Gamma=Gamma)
  sun3 <- makeSUNdistr(dp=dp3, name="firstSUN", compNames=c("x", "w", "z"))
  show(sun3)
  plot(sun3)
  mean(sun3)  # the mean value of the probability distribution
  vcov(sun3)  # the variance-covariance matrix of the probability distribution
  summary(sun3)  # a more detailed summary

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