stephensrmmartin

library(shiny)
library(ggvis)
colors <- c('black','red','blue','green')
shinyServer(function(input, output, session) {
		dsR <- reactive({
			invalidateLater(input$refresh, session);
			data.frame(Value = rnorm(n = input$nObs, mean = input$mean, sd = input$sd))	
		})
		
		gv <- reactive({

stephensrmmartin

library(shiny)
library(ggvis)

colors <- c('black','red','green','grey')
shinyServer(function(input, output,session) {
	population0 <- reactive({
		data.frame(Value = rnorm(n = 100000,mean = input$mu0,sd = input$sigma0))
	})
	
	population1 <- reactive({

stephensrmmartin

# Maintainer: Stephen Martin <stephenSRMMartin at gmail dot com>
pkgname=jasp-desktop-git
_pkgname=jasp-desktop
_buildname=jasp-build
pkgver=r1752.1a28614
pkgrel=1
pkgdesc="JASP, a low fat alternative to SPSS, a delicious alternative to R."
arch=('any')
url="http://jasp-stats.org"
license=('AGPL3')

stephensrmmartin

---
title: "Bayesian SEM example"
output: html_notebook
---

The example below will use the "Political Democracy" dataset from the lavaan package.
```{r}
library(lavaan)
library(rstan)
options(mc.cores=4)

stephensrmmartin

data {
	int N;
	vector[N] read; // Data vectors
	vector[N] parents;
	vector[N] ses;
	vector[N] iq;
	vector[N] treat;

	int read_nMiss; // N missing from variables; excluded have no missings
	int ses_nMiss;

stephensrmmartin

functions {
  real matrix_f_lpdf(matrix cov, real nu, real delta){
    int k = cols(cov);
    return(lmgamma(k, (nu + delta + k - 1)/2) - (lmgamma(k, nu/2) + lmgamma(k, (delta + k - 1)/2) + log(1)) + log_determinant(cov)*((nu -k - 1)/2) - (nu + delta + k - 1)/2 * log_determinant(cov + diag_matrix(rep_vector(1, k))));
  }
  
  real matrix_f_fast_lpdf(matrix cov, real nu, real delta){
    int k = cols(cov);
    real log_det_cov = 2*sum(log(diagonal(cholesky_decompose(cov))));
    real I_Sig_log_det = 2*sum(log(diagonal(cholesky_decompose(diag_matrix(rep_vector(1,k)) + cov))));