Simulate data distributed according to oHMMed with normal emission densities

Usage

hmm_simulate_normal_data(L, mat_T, means, sigma)

Arguments

L: (integer) number of simulations
mat_T: (matrix) a square matrix with the initial state
means: (numeric) mean parameter in rnorm for emission probabilities
sigma: (numeric) sd parameter in rnorm for emission probabilities

Value

Returns a list with the following elements:

data: numeric vector with data
states: an integer vector with "true" hidden states used to generate the data vector
pi: numeric vector with prior probability of states

Examples

mat_T0 <- rbind(c(1-0.01, 0.01, 0),
                c(0.01, 1-0.02, 0.01),
                c(0, 0.01, 1-0.01))
L <- 2^7
means0 <- c(-1,0,1)
sigma0 <- 1

sim_data <- hmm_simulate_normal_data(L = L, 
                                     mat_T = mat_T0, 
                                     means = means0, 
                                     sigma = sigma0)
                                     
plot(density(sim_data$data), main = "Density of Simulated Normal Data")

sim_data
#> $data
#>   [1] -0.06864381 -3.52368000 -0.26801732 -1.82100090 -1.11234527 -1.42891536
#>   [7] -0.32001136  2.19661376 -0.28734881  0.50418329 -0.56098588 -0.78995781
#>  [13] -0.71556271 -0.16015369  1.49216131 -1.57180982 -0.73566420  1.04277799
#>  [19] -1.07743443  0.57081259  1.97377167 -1.01163052 -0.70553719  0.79925384
#>  [25]  0.32294219  0.74904887  0.16590734 -0.65343176 -0.98416503  0.16364040
#>  [31]  0.93685363  1.64695220  1.16516140 -0.56124951 -0.38728808 -1.24761866
#>  [37] -0.06821972 -2.07662407 -0.08556544 -2.34239847 -1.40870352 -0.24489081
#>  [43]  0.05579589 -0.58992833 -1.08932963 -0.15785072  1.60267101 -0.24672514
#>  [49]  0.62279916 -0.75373738 -0.18716072 -0.46718535 -0.04951256  1.48998726
#>  [55]  0.25838011 -1.34872803 -0.58619822 -0.59120157  0.39377320  0.35538519
#>  [61] -0.52964962  1.11280893  0.80504476 -1.84203046 -0.57520477  0.83992653
#>  [67] -1.22094483 -0.24063909 -0.89528027 -2.01216892 -1.87995892 -0.07418819
#>  [73] -1.60831759 -0.62135704 -2.48994977 -1.29551415 -0.83745039 -2.22804403
#>  [79] -1.07123827 -1.09225574 -0.95110838 -2.07033987 -1.26392179 -0.81904785
#>  [85]  0.71105378 -0.02091522 -2.22040639  0.53415880 -2.51269548 -0.20257148
#>  [91] -2.16915431  0.36747742  0.05930010 -0.79773002 -1.60113573 -1.66390738
#>  [97] -1.92386162 -1.45795126 -1.05795807 -1.80692064 -2.35199888 -2.94379693
#> [103] -1.03045446 -0.57521002 -2.65885216  0.08131543 -1.20078062 -0.78831543
#> [109]  0.62809542 -1.66606811 -1.31006712 -0.31413213 -2.08066035 -1.97584998
#> [115] -1.61461344 -0.91449988 -1.95952440 -0.35792333 -3.04353756 -1.25287248
#> [121]  0.19179717 -1.12988155 -0.85175299 -2.73620340 -2.57813407 -1.55311971
#> [127] -1.11843851 -0.62378240
#> 
#> $states
#>   [1] 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1
#>  [38] 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1
#>  [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> [112] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> Levels: 1 2 3
#> 
#> $pi
#> [1] 0.3333333 0.3333333 0.3333333
#>