gendata_cmgfm {CMGFM}

Generate simulated data

Description

Generate simulated data from covariate-augumented generalized factor model

Usage

gendata_cmgfm(
  seed = 1,
  n = 300,
  pveclist = list(gaussian = c(50, 150), poisson = c(50), binomial = c(100, 60)),
  q = 6,
  d = 3,
  rho = rep(1, length(pveclist)),
  rho_z = 1,
  sigmavec = rep(0.5, length(pveclist)),
  n_bin = 1,
  sigma_eps = 1,
  seed.para = 1
)

Arguments

seed

a positive integer, the random seed for reproducibility of data generation process.

n

a positive integer, specify the sample size.

pveclist

a named list, specify the number of modalities for each variable type and dimension of variables in each modality.

q

a positive integer, specify the number of modality-shared factors.

d

a positive integer, specify the dimension of covariate matrix.

rho

a numeric vector with length length(pveclist) and positive elements, specify the signal strength of loading matrix for each modality with the same variable type.

rho_z

a positive real, specify the signal strength of covariates.

sigmavec

a positive vector with length length(pveclist), the variance of modality-specified latent factors.

n_bin

a positive integer, specify the number of trails in Binomial distribution.

sigma_eps

a positive real, the variance of overdispersion error.

seed.para

a positive integer, the random seed for reproducibility of data generation process by fixing the regression coefficient vector and loading matrices.

Details

None

Value

return a list including the following components:

• XList - a list consisting of multiple matrices in which each matrix has the same type of values, i.e., continuous, or count, or binomial/binary values.

• Z - a matrix, the fixed-dimensional covariate matrix with control variables;

• Alist - the the offset vector for each modality;

• B0list - the true loading matrix for each modality;

• mu0 - the true intercept vector for each modality;

• U0 - the modality-specified factor vector;

• F0 - the modality-shared factor matrix;

• Uplist - the true intercept-loading matrix for each modality;

• beta - the true regression coefficient vector for each modality;

• sigma_eps - the standard deviation of error term;

• numvarmat - a length(types)-by-d matrix, the number of variables in modalities that belong to the same type.

References

None

See Also

CMGFM

Examples

n <- 300; 
pveclist = list('gaussian'=c(50, 150),'poisson'=c(50),'binomial'=c(100,60))
d <- 20; q <- 6;
datlist <- gendata_cmgfm(n=n, pveclist=pveclist, q=q, d=d)
str(datlist)