added bugs_example/vol1/litter files

Author: PeterLi2016

bugs_examples/vol1/litter/litter.data.R

@@ -0,0 +1,9 @@
+G <- 2
+N <- 16
+r <- 
+structure(c(13, 12, 12, 11, 9, 10, 9, 9, 8, 10, 8, 9, 12, 9, 11, 8, 9, 8, 9, 4, 8, 7, 11, 4, 4, 5, 5, 3, 7, 3, 7, 0),
+.Dim = c(2, 16))
+n <- 
+structure(c(13, 12, 12, 11, 9, 10, 9, 9, 8, 11, 8, 10, 13, 10, 12, 9, 10, 9, 10, 5, 9, 9, 13, 7, 5, 10, 7, 6, 10, 10,
+10, 7),
+.Dim = c(2, 16))

bugs_examples/vol1/litter/litter_reparam.stan

@@ -0,0 +1,31 @@
+data {
+  int<lower=0> G;
+  int<lower=0> N;
+  int<lower=0> r[G,N];
+  int<lower=0> n[G,N];
+}
+parameters {
+  matrix<lower=0,upper=1>[G,N] p;
+  vector<lower=0,upper=1>[G] mu;
+  vector<lower=0.1>[G] a_plus_b;
+}
+transformed parameters {
+  vector[G] a;
+  vector[G] b;
+  a <- mu .* a_plus_b;
+  b <- (1 - mu) .* a_plus_b;
+}
+model {
+  a_plus_b ~ pareto(0.1,1.5);
+  for (g in 1:G) {
+    for (i in 1:N) { 
+      p[g,i] ~ beta(a[g],b[g]);
+      r[g,i] ~ binomial(n[g,i],p[g,i]);
+    }
+  }      
+}
+generated quantities {
+  vector<lower=0>[G] theta;
+  for (g in 1:G)
+    theta[g] <- 1 / (a[g] + b[g]);
+}

bugs_examples/vol1/litter/makefile

@@ -0,0 +1,15 @@
+STAN_HOME = ../../../../..
+PGM = litter#
+CXX = g++  
+BOOSTPATH = $(shell find $(STAN_HOME)/lib -path '*lib/boost_*' -regex '.*lib\/boost_[^/]*')
+EIGENPATH = $(shell find $(STAN_HOME)/lib -path '*lib/eigen_*' -regex '.*lib\/eigen_[^/]*')
+CPPFLAGS = -I $(BOOSTPATH)  -I$(EIGENPATH) -I $(STAN_HOME)/src
+LIBFLAGS = -L$(STAN_HOME)/bin -lstan 
+
+$(PGM) :
+	$(STAN_HOME)/bin/stanc --name=$(PGM)  $(PGM).stan 
+	$(CXX) -O3 -DNDEBUG  $(CPPFLAGS) $(PGM).cpp -o $(PGM) $(LIBFLAGS)
+	./$(PGM) data=$(PGM).data.R sample 
+
+clean :
+	rm -rf $(PGM).cpp samples.csv $(PGM) 

bugs_examples/vol1/litter/post.R

@@ -0,0 +1,25 @@
+## take a look at the samples and compare with results computed 
+## in other program. 
+
+
+library(coda) 
+
+post <- read.csv(file = "samples.csv", header = TRUE, comment.char = '#');
+
+summary(as.mcmc(poi)) 
+
+library(BUGSExamples)
+
+
+# theta0 <- theta[1] - theta[2] * mean(X) 
+ex <- list(name = "Litter", parameters = pars, 
+           nSample = 10000, nBurnin = 1000, nThin = 1, 
+           nChain = 3); 
+
+jagspost <- runExample(ex, engine = 'JAGS') 
+summary(jagspost$coda) 
+
+
+
+
+