Ch6 models

Author: Andrew Johnson

ARM/Ch.6/earnings1.stan

@@ -4,10 +4,13 @@ data {
   vector[N] height;
   vector[N] male;
 } 
+transformed data {
+  matrix[N,2] x = [height', male']';
+}
 parameters {
-  vector[3] beta;
-  real<lower=0> sigma;
+  real alpha;
+  vector[2] beta;
 } 
 model {
-  earn_pos ~ bernoulli_logit(beta[1] + beta[2] * height + beta[3] * male);
+  earn_pos ~ bernoulli_logit_glm(x, alpha, beta);
 }

ARM/Ch.6/earnings2.stan

@@ -5,16 +5,15 @@ data {
   vector[N] sex;
 } 
 transformed data {
-  vector[N] log_earnings;
-  vector[N] male;
-
-  log_earnings = log(earnings);
-  male = 2 - sex;
+  vector[N] log_earnings = log(earnings);
+  vector[N] male = 2 - sex;
+  matrix[N,2] x = [height', male']';
 }
 parameters {
-  vector[3] beta;
+  real alpha;
+  vector[2] beta;
   real<lower=0> sigma;
 } 
 model {
-  log_earnings ~ normal(beta[1] + beta[2] * height + beta[3] * male, sigma);
+  log_earnings ~ normal_id_glm(x, alpha, beta, sigma);
 }

ARM/Ch.6/wells_logit.stan

@@ -4,13 +4,13 @@ data {
   int<lower=0,upper=1> switc[N];
 }
 transformed data {
-  vector[N] dist100;
-
-  dist100 = dist / 100.0;
+  vector[N] dist100 = dist / 100.0;
+  matrix[N,1] x = [dist100']';
 }
 parameters {
-  vector[2] beta;
+  real alpha;
+  vector[1] beta;
 } 
 model {
-  switc ~ bernoulli_logit(beta[1] + beta[2] * dist100);
-}
+  switc ~ bernoulli_logit_glm(x, alpha, beta);
+}

ARM/Ch.6/wells_probit.stan

@@ -4,14 +4,13 @@ data {
   int<lower=0,upper=1> switc[N];
 }
 transformed data {
-  vector[N] dist100;
-
-  dist100 = dist / 100.0;
+  vector[N] dist100 = dist / 100.0;
+  matrix[N,1] x = [dist100']';
 }
 parameters {
-  vector[2] beta;
+  real alpha;
+  vector[1] beta;
 } 
 model {
-  for (n in 1:N)
-    switc[n] ~ bernoulli(Phi(beta[1] + beta[2] * dist100[n]));
-}
+  switc ~ bernoulli(Phi(alpha + x * beta));
+}