rmsen {SenTinMixt}

Random number generation for the MSEN distribution

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)