simulate_zero_inflated_beta_random_effect_data: Simulate data according to zero-inflated beta random effects...

In chvlyl/ZIBRE: A Zero-Inflated Beta Random Effect Model

Simulate data according to zero-inflated beta random effects model

Description

Simulate data according to zero-inflated beta random effects model

Usage

simulate_zero_inflated_beta_random_effect_data(
  subject_n = 50,
  time_n = 5,
  v = 2,
  alpha = as.matrix(c(0, 0.5, -1)),
  beta = as.matrix(c(-0.5, -0.5, 0.5)),
  X = NA,
  Z = NA,
  s1 = 0.2,
  s2 = 0.2,
  sim_seed = 100
)

Arguments

subject_n	number of subjects
time_n	number of time points for each subject
v	the dispersion parameter in beta component
alpha	the coefficients in logistic component
beta	the coefficients in beta component
X	the covariates in logistic component
Z	the covariates in beta component
s1	the stardard deviation of random effect in logistic component
s2	the stardard deviation of random effect in beta component
sim_seed	the random seed

Value

a named list

• Y the bacterial abundance generated from the model

• X the covariates in logistic component

• Z the covariates in beta component

• alpha the coefficients in logistic component

• beta the coefficients in beta component

• s1 the stardard deviation of random effect in logistic component

• s2 the stardard deviation of random effect in beta component

• subject_ind the IDs for each subject

• time_ind time points

Examples

simulate_zero_inflated_beta_random_effect_data(
  subject_n = 100, time_n = 5,
  X = as.matrix(c(rep(0, 50 * 5), rep(1, 50 * 5))),
  alpha = as.matrix(c(-0.5, 1)),
  beta = as.matrix(c(-0.5, 0.5)),
  s1 = 1, s2 = 0.8,
  v = 5,
  sim_seed = 100
)

chvlyl/ZIBRE documentation built on Oct. 22, 2023, 1:06 p.m.