Fitting synthetic data

This is an example of fitting pseudo data for the paper

Kuha, J., Zhang, S., & Steele, F. (2021). Latent variable models for multivariate dyadic data with zero inflation: Analysis of intergenerational exchanges of family support.

##############################################
## Load synthetic data

rm(list = ls())
load(url("https://github.com/slzhang-fd/jsem-ukhls/blob/main/inst/UKHLS_synthetic.rda?raw=true"))

##############################################
## Load jsem package

library(jsem)

##############################################
## Fit full model

mod_f <- formula(~ female + partnerinhh + emp_unemployed + emp_inactive +
  cany + cy_2to4 + cy_5to10 + cy_11to16 + cy_gt16 + age40 +
  parmaxage70 + palone + distlong + nsibs12 + nsibs3plus + logincome)

##############################################
## It takes about 3 hrs for the following MCMC length settings
## A shorter length may be chosen to save some time

pseudo_data_res <-
  dylanie_model_simple(mod_f, data = pseudo_data, mcmc_len = 1000)

pseudo_data_res <- 
  dylanie_model_update(pseudo_data_res, mcmc_len = 9000)