rMixt {SenTinMixt} | R Documentation |
Random number generation for bidimensional parsimonious mixtures of MSEN or MTIN distributions
Description
Random number generation for bidimensional parsimonious mixtures of MSEN or MTIN distributions
Usage
rMixt(n, k, Pi, mu, cov.model, lambda, delta, gamma, theta, density)
Arguments
n |
An integer specifying the number of data points to be simulated. |
k |
An integer indicating the number of groups in the data. |
Pi |
A vector of length |
mu |
A matrix of means with 2 rows and |
cov.model |
A character indicating the parsimonious structure of the scale matrices. Possible values are: "EII", "VII", "EEI", "VEI", "EVI", "VVI", "EEE", "VEE", "EVE", "EEV", "VVE", "VEV", "EVV" or "VVV". |
lambda |
A numeric vector of length |
delta |
A numeric vector of length |
gamma |
A numeric vector of length |
theta |
A vector of length |
density |
A character indicating the density of the mixture components. Possible values are: "MSEN" or "MTIN". |
Value
A list with the following elements:
X |
A data matrix with |
Sigma |
An array of dimension 2 x 2 x |
Size |
The size of each generated group. |
References
Punzo A., Browne R. and McNicholas P.D. (2016). Hypothesis Testing for Mixture Model Selection. Journal of Statistical Computation and Simulation, 86(14), 2797-2818.
Examples
n <- 50
k <- 2
Pi <- c(0.5, 0.5)
mu <- matrix(c(0, 0, 4, 5), 2, 2)
cov.model <- "EEE"
lambda <- c(0.5, 0.5)
delta <- c(0.7, 0.7)
gamma <- c(2.62, 2.62)
theta <- c(0.1, 0.1)
density <- "MSEN"
data <- rMixt(n, k, Pi, mu, cov.model, lambda, delta, gamma, theta, density)