---
title: "Package lchemix"
author: "Zhen Chen, Beom Seuk Hwang, Germaine M. Buck Louis, Paul S. Albert, Weimin Zhang" 
date: "`r Sys.Date()`" 
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Package lchemix}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(lchemix)

```
Description: fit a couple-based joint latent class model with an interaction between a
 couple(e.g., female and male partners) and High-dimensional semicontinuous chemical biomarker
 for each partner of the couple. This formulation introduces a dependence structure between the chemical
 patterns within a couple and between the chemical patterns and the risk of desease.
 A Bayesian framework examines the chemical biomarker profile from each member of the couple
 and the risk of disease. The complex chemical mixtures on each couple link to disease risk through unobserved
 latent classes. we posit that two sets of latent classes, each characterizing the chemical mixture patterns
 of one partner of the couple, are linked to the risk of disease through a logistic model with main and
 interaction  effects between latent classes. The semicontinuous chimical biomarker viarables (1/4 zeros and
 right-skewed non-zero values) are processed through Tobit modeling framework. Markov chain Monte Carlo
 algorithms was used to obtain posterior estimates of model parameters.The user supplies data and priors,
 and a list of posterior estimates of model parameters is returned.