rmsen: Random number generation for the MSEN distribution

In SenTinMixt: Parsimonious Mixtures of MSEN and MTIN Distributions

Description

Random number generation for the MSEN distribution

Usage

rmsen(n, mu = rep(0, d), Sigma, theta = Inf)

Arguments

n	An integer specifying the number of data points to be simulated.
mu	A vector of length d, where d is the dimensionality, representing the mean value.
Sigma	A symmetric positive-definite matrix representing the scale matrix of the distribution.
theta	A number greater than 0 indicating the tailedness parameter.

Value

A list with the following elements:

X	A data matrix with n rows and d columns.
w	A vector of weights of dimension n.

References

Punzo A., and Bagnato L. (2020). Allometric analysis using the multivariate shifted exponential normal distribution. Biometrical Journal, 62(6), 1525-1543.

Examples

d <- 3
rmsen(10, mu = rep(0, d), Sigma = diag(d), theta = 0.3)

SenTinMixt documentation built on Oct. 20, 2021, 9:07 a.m.