Merge branch 'master' of https://github.com/stan-dev/example-models

Author: mitzimorris

ARM/Ch.17/latent_glm_17.7.data.R

@@ -16,7 +16,6 @@ data {
   vector[N] z;
 }
 parameters {
-  real<lower=0> sigma;
   real<lower=0> sigma_age;
   real<lower=0> sigma_edu;
   real<lower=0> sigma_state;
@@ -47,6 +46,12 @@ model {
   b_female ~ normal(0, 100);
   b_black ~ normal(0, 100);
   b_female_black ~ normal(0, 100);
+  
+  sigma_age ~ normal(0, 10);
+  sigma_edu ~ normal(0, 10);
+  sigma_state ~ normal(0, 10);
+  sigma_region ~ normal(0, 10);
+  sigma_age_edu ~ normal(0, 10);
 
   b_age ~ normal(0, sigma_age);
   b_edu ~ normal(0, sigma_edu);

ARM/Ch.17/latent_glm_17.7.stan

@@ -0,0 +1,45 @@
+N <-
+100
+n_cut <-
+2
+n_player <-
+5
+player <-
+c(3, 2, 1, 2, 4, 3, 3, 5, 5, 3, 3, 3, 4, 5, 5, 4, 5, 2, 2, 4, 
+2, 3, 2, 2, 1, 5, 3, 5, 4, 4, 4, 5, 3, 5, 2, 4, 1, 2, 4, 4, 5, 
+5, 3, 2, 2, 2, 1, 2, 4, 2, 3, 2, 5, 1, 1, 1, 5, 2, 3, 2, 4, 2, 
+2, 5, 4, 1, 4, 2, 1, 5, 3, 2, 5, 5, 5, 2, 1, 4, 1, 5, 4, 2, 1, 
+3, 2, 3, 2, 3, 2, 1, 1, 1, 3, 4, 5, 4, 3, 2, 5, 1)
+y <-
+c(1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 1, 
+2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 2, 1, 
+1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 2, 1, 1, 2, 1, 1, 
+1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 
+1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 1)
+x <-
+c(0.876459347549826, 0.94552709441632, 0.379680620040745, 0.219244197010994, 
+0.032204027986154, 0.501873050816357, 0.91952364356257, 0.204486317699775, 
+0.465604034485295, 0.193179059308022, 0.807848534779623, 0.136463716626167, 
+0.58082992141135, 0.522358619142324, 0.249525807099417, 0.747587669175118, 
+0.561783782904968, 0.707277777139097, 0.252917441539466, 0.319943462032825, 
+0.175028294324875, 0.575390010140836, 0.751595235429704, 0.506773706758395, 
+0.822272704914212, 0.883299466455355, 0.122583804884925, 0.612658169353381, 
+0.399398803943768, 0.519211766542867, 0.553035432705656, 0.364366877824068, 
+0.990204400382936, 0.979995706351474, 0.274602472083643, 0.946819088887423, 
+0.67284260247834, 0.994728937977925, 0.292697216849774, 0.0111141889356077, 
+0.797478761291131, 0.472787593025714, 0.0889191201422364, 0.730681328568608, 
+0.993295247200876, 0.0910165079403669, 0.541658846195787, 0.167015166254714, 
+0.199509128928185, 0.420785219874233, 0.111460458487272, 0.78926312783733, 
+0.627885694848374, 0.465886945603415, 0.684862856054679, 0.270942791132256, 
+0.202441103756428, 0.977098781382665, 0.606753138359636, 0.81810313090682, 
+0.062712682178244, 0.691455142339692, 0.925387117313221, 0.915808056248352, 
+0.0373755777254701, 0.416192142991349, 0.197934444760904, 0.522862639278173, 
+0.3995981158223, 0.207565931836143, 0.766014510998502, 0.225867514265701, 
+0.985176953254268, 0.0127217643894255, 0.412924433825538, 0.272256464697421, 
+0.51302864542231, 0.179800998419523, 0.771019102074206, 0.832560452399775, 
+0.0185076335910708, 0.918299656594172, 0.3187188974116, 0.878578629344702, 
+0.660703920759261, 0.0978191271424294, 0.676573234377429, 0.714977518422529, 
+0.25360164558515, 0.315959327388555, 0.826745369005948, 0.402351861121133, 
+0.698947778204456, 0.410614568740129, 0.34994190488942, 0.143103830749169, 
+0.421381167601794, 0.97658223612234, 0.909887991845608, 0.129774280125275
+)

ARM/Ch.17/multilevel_ordered_categorical_17.6.data.R

@@ -20,10 +20,13 @@ parameters {
 model {
   real mu_adj;
   matrix[N,n_cut] Q;
-  matrix[N,n_cut] P;
+  matrix[N,n_cut+1] P;
 
   mu_c ~ normal(0, 1000);
   mu_log_s ~ normal(0, 100);
+  
+  sigma_c ~ normal(0, 10);
+  sigma_log_s ~ normal(0, 10);
 
   for (i in 1:n_player) {
     C[i,1] ~ normal(mu_c[1], sigma_c[1]) T[0,C[i,2]];

ARM/Ch.17/multilevel_ordered_categorical_17.6.stan

@@ -26,6 +26,10 @@ model {
 
   mu ~ normal(0, 100);
   mu_adj = mu + mean(b_eth) + mean(b_precint);
+  
+  sigma_epsilon ~ normal(0, 10);
+  sigma_eth ~ normal(0, 10);
+  sigma_precint ~ normal(0, 10);
 
   b_eth ~ normal(0, sigma_eth);
   b_eth_adj = b_eth - mean(b_eth);
@@ -41,3 +45,5 @@ model {
 
   stops ~ poisson_log(lambda);
 }
+// Information on the data can be found in this blog:
+// http://www.clayford.net/statistics/poisson-regression-ch-6-of-gelman-and-hill/

ARM/Ch.17/multilevel_poisson_17.5.data.R

@@ -12,8 +12,8 @@ data {
   int<lower=0, upper=n_state> region[n_state];
   int<lower=0, upper=n_state> state[N];
   int<lower=0, upper=1> y[N];
-  vector[N] z;
-  vector[N] v_prev;
+  vector[N] z; // latent variable initialisation values
+  vector[n_state] v_prev;
 }
 parameters {
   real<lower=0> sigma_age;
@@ -48,6 +48,12 @@ model {
   b_female ~ normal(0, 100);
   b_black ~ normal(0, 100);
   b_female_black ~ normal(0, 100);
+  
+  sigma_age ~ normal(0, 10);
+  sigma_edu ~ normal(0, 10);
+  sigma_state ~ normal(0, 10);
+  sigma_region ~ normal(0, 10);
+  sigma_age_edu ~ normal(0, 10);
 
   b_age ~ normal(0, sigma_age);
   b_edu ~ normal(0, sigma_edu);