gendata_mmgfm {MMGFM} | R Documentation |
Generate simulated data from MMGFM models
gendata_mmgfm(
seed = 1,
nvec = c(300, 200),
pveclist = list(gaussian = c(50, 150), poisson = c(50), binomial = c(100, 60)),
q = 6,
d = 3,
qs = rep(2, length(nvec)),
rho = rep(1, length(pveclist)),
rho_z = 1,
sigmavec = rep(0.5, length(pveclist)),
n_bin = 1,
sigma_eps = 1,
heter_error = FALSE
)
seed |
a postive integer, the random seed for reproducibility of data generation process. |
nvec |
a vector with postive integers, specify the sample size in each study/source. |
pveclist |
a named list, specify the number of modalities for each type and variable dimension in each type of modatlity. |
q |
a postive integer, specify the number of study-shared factors. |
d |
a postive integer, specify the dimension of covariate matrix. |
qs |
a vector with postive integers, specify the number of study-specified factors. |
rho |
a numeric vector with |
rho_z |
a positive real, specify the signal strength of covariates. |
sigmavec |
a positive real vector with |
n_bin |
a positive integer, specify the number of trails when generate Binomial modality matrix; default as 1. |
sigma_eps |
a positive real, the variance of overdispersion error; default as 1. |
heter_error |
a logical value, whether to generate the heterogeneous error; default as FALSE. |
return a list including the following components:
hbeta
- a M-length list composed by the estimated regression coefficient matrix for each modality;
hA
- a M-length list composed by the loading matrix corresponding to study-shared factors for each modality;
hB
- a S-length list composed by a M-length loading matrix list corresponding to study-specified factors for each study;
hF
- a S-length list composed by the posterior estimation of study-shared factor matrix for each study;
hH
- a S-length list composed by the posterior estimation of study-specified factor matrix for each study;
hSigma
- a S-length list composed by the estimated posterior variance of the study-shared factor;
hPhi
- a S-length list composed by the estimated posterior variance of study-specified factor;
hv
- a S-length list composed by a M-length vector list corresponding to the posterior estimation of study-specified and modality variable-shared factor for each study and modality;
hzeta
- the estimated posterior variance for study-specified and modality variable-shared factor;
hsigma2
- the estimated variance for study-specified and modality variable-shared factor;
hinvLambda
- a S-length list composed by a M-length vector list corresponding to the inverse of the estimated variances of error;
S
- the approximated posterior covariance for each row of F;
ELBO
- the ELBO value when algorithm stops;
ELBO_seq
- the sequence of ELBO values.
time_use
- the running time in model fitting of SpaCOAP;
q <- 3; qsvec<-rep(2,3)
nvec <- c(100, 120, 100)
pveclist <- list('gaussian'=rep(150, 1),'poisson'=rep(50, 2),'binomial'=rep(60, 2))
datlist <- gendata_mmgfm(seed = 1, nvec = nvec, pveclist =pveclist,
q = q, d= 3,qs = qsvec, rho = rep(3,length(pveclist)), rho_z=0.5,
sigmavec=rep(0.5, length(pveclist)), sigma_eps=1)