rmixmvnorm function

Random data generation from the mixture of multivariate normals for hhsmm model

Random data generation from the mixture of multivariate normals for hhsmm model

Generates a vector of observations from mixture multivariate normal distribution in a specified state and using the parameters of a specified model

rmixmvnorm(j, model)

Arguments

  • j: a specified state
  • model: a hhsmmspec model

Returns

a random vector of observations from mixture of multivariate normal distributions

Examples

J <- 3 initial <- c(1, 0, 0) semi <- c(FALSE, TRUE, FALSE) P <- matrix(c(0.8, 0.1, 0.1, 0.5, 0, 0.5, 0.1, 0.2, 0.7), nrow = J, byrow = TRUE) par <- list(mu = list(list(7, 8), list(10, 9, 11), list(12, 14)), sigma = list(list(3.8, 4.9), list(4.3, 4.2, 5.4), list(4.5, 6.1)), mix.p = list(c(0.3, 0.7), c(0.2, 0.3, 0.5), c(0.5, 0.5))) sojourn <- list(shape = c(0, 3, 0), scale = c(0, 10, 0), type = "gamma") model <- hhsmmspec(init = initial, transition = P, parms.emis = par, dens.emis = dmixmvnorm, sojourn = sojourn, semi = semi) x = rmixmvnorm(1, model)

Author(s)

Morteza Amini, morteza.amini@ut.ac.ir , Afarin Bayat, aftbayat@gmail.com

  • Maintainer: Morteza Amini
  • License: GPL-3
  • Last published: 2024-09-04

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