tests/testthat/test-roxytest-testexamples-smmparametric.R

In corentin-dev/smmR: Simulation, Estimation and Reliability of Semi-Markov Models

# Generated by roxytest: Do not edit by hand!

context("File R/smmparametric.R: @testexamples")

test_that("Function smmparametric() @ L149", {
  
  states <- c("a", "c", "g", "t")
  s <- length(states)
  
  # Creation of the initial distribution
  vect.init <- c(1 / 4, 1 / 4, 1 / 4, 1 / 4)
  
  # Creation of the transition matrix
  pij <- matrix(c(0, 0.2, 0.5, 0.3,
                  0.2, 0, 0.3, 0.5,
                  0.3, 0.5, 0, 0.2,
                  0.4, 0.2, 0.4, 0),
                ncol = s, byrow = TRUE)
  
  # Creation of the distribution matrix
  
  distr.matrix <- matrix(c(NA, "pois", "geom", "nbinom",
                           "geom", NA, "pois", "dweibull",
                           "pois", "pois", NA, "geom",
                           "pois", "geom", "geom", NA),
                         nrow = s, ncol = s, byrow = TRUE)
  
  # Creation of an array containing the parameters
  param1.matrix <- matrix(c(NA, 2, 0.4, 4,
                            0.7, NA, 5, 0.6,
                            2, 3, NA, 0.6,
                            4, 0.3, 0.4, NA),
                          nrow = s, ncol = s, byrow = TRUE)
  
  param2.matrix <- matrix(c(NA, NA, NA, 0.6,
                            NA, NA, NA, 0.8,
                            NA, NA, NA, NA,
                            NA, NA, NA, NA),
                          nrow = s, ncol = s, byrow = TRUE)
  
  param.array <- array(c(param1.matrix, param2.matrix), c(s, s, 2))
  
  # Specify the semi-Markov model
  semimarkov <- smmparametric(states = states, init = vect.init, ptrans = pij, 
                              type.sojourn = "fij", distr = distr.matrix, 
                              param = param.array)
  semimarkov
  
  expect_true(all(semimarkov$init - vect.init == 0))
  expect_true(all(semimarkov$ptrans - pij == 0))
  expect_true(is.smm(semimarkov))
  expect_true(is.smmparametric(semimarkov))
  expect_false(is.smmnonparametric(semimarkov))
})