simulate_data: simulate data from restricted latent class models
In oslerinhealth/rewind: Reconstructing Etiology with Binary Decomposition

Description Usage Arguments Value Examples

This function takes in options_sim and simulate as specified by the options. NB: currently only supports logical "Or", or DINO model. Other restricted latent class models need to be added. NB: alpha1 needs to be update

1	simulate_data(options_sim, SETSEED = FALSE)

options_sim

options for simulating data:

N - sample size;
M - number of machines;
L - number of protein landmarks;
K - number of ture components;
alpha1 - hyperparameter for determining the machine prevalence p_m; (NB: delete?)
theta - true positive rates for all protein landmarks;
psi - false positive rates for all protein landmarks.
frac - Percentage of (L-2M) dimensions that are positive in Q; See simulate_Q.
pop_frac - population prevalences of the K components.

SETSEED

FALSE by default; Set to TRUE if to fix random number generation.

datmat a matrix for multivariate binary observations from the assumed boolean matrix factorization,
Q A Q-matrix,
H_star A binary matrix of dimension K by M, for K clusters, and M latent states,
Z A vector of length N for individual cluster indicators,
xi a binary matrix of dimension N by L for true presence or absence of proteins
Eta A binary matrix of dimension N by M for presence or absence of latent states among all subjects.

# simulate data:
L0 <- 100
options_sim0  <- list(N = 200,  # sample size.
                     M = 3,   # true number of machines.
                     L = L0,   # number of antibody landmarks.
                     K = 8,    # number of true components.,
                     theta = rep(0.8,L0), # true positive rates
                     psi   = rep(0.01,L0), # false positive rates
                     alpha1 = 1 # half of the people have the first machine.
)

simu     <- simulate_data(options_sim0, SETSEED=TRUE)
simu_dat <- simu$datmat
image(simu_dat)