Merge pull request #195 from andrjohns/feature/arm_ch5

rok-cesnovar · web-flow · commit 241de2cb9f2c · 2021-02-06T16:36:31.000+01:00
Update ARM Ch.5 Models
diff --git a/ARM/Ch.5/nes_logit.stan b/ARM/Ch.5/nes_logit.stan
@@ -3,9 +3,13 @@ data {
   vector[N] income;
   int<lower=0,upper=1> vote[N];
 }
+transformed data {
+  matrix[N,1] x = [income']';
+}
 parameters {
-  vector[2] beta;
+  real alpha;
+  vector[1] beta;
 }
 model {
-  vote ~ bernoulli_logit(beta[1] + beta[2] * income);
+  vote ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/separation.stan b/ARM/Ch.5/separation.stan
@@ -1,11 +1,12 @@
 data {
   int<lower=0> N;
   int<lower=0,upper=1> y[N];
-  vector[N] x;
+  matrix[N,1] x;
 }
 parameters {
-  vector[2] beta;
+  real alpha;
+  vector[1] beta;
 }
 model {
-  y ~ bernoulli_logit(beta[1] + beta[2] * x);
+  y ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_d100ars.stan b/ARM/Ch.5/wells_d100ars.stan
@@ -5,12 +5,14 @@ data {
   vector[N] arsenic;
 }
 transformed data {
-  vector[N] dist100;         // rescaling
-  dist100 = dist / 100.0;
+  // rescaling
+  vector[N] dist100 = dist / 100.0;
+  matrix[N,2] x = [dist100', arsenic']';
 }
 parameters {
-  vector[3] beta;
+  real alpha;
+  vector[2] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * dist100 + beta[3] * arsenic);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_daae_c.stan b/ARM/Ch.5/wells_daae_c.stan
@@ -7,20 +7,17 @@ data {
   vector[N] educ;
 }
 transformed data {
-  vector[N] c_dist100;
-  vector[N] c_arsenic;
-  vector[N] da_inter;
-  vector[N] educ4;
-  c_dist100 = (dist - mean(dist)) / 100.0;
-  c_arsenic = arsenic - mean(arsenic);
-  da_inter  = c_dist100 .* c_arsenic;
-  educ4     = educ / 4.0;
+  vector[N] c_dist100 = (dist - mean(dist)) / 100.0;
+  vector[N] c_arsenic = arsenic - mean(arsenic);
+  vector[N] da_inter = c_dist100 .* c_arsenic;
+  vector[N] educ4 = educ / 4.0;
+  matrix[N,5] x = [c_dist100', c_arsenic', da_inter',
+                   assoc', educ4']';
 }
 parameters {
-  vector[6] beta;
+  real alpha;
+  vector[5] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * c_dist100 + beta[3] * c_arsenic
-                              + beta[4] * da_inter + beta[5] * assoc 
-                              + beta[6] * educ4);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_dae.stan b/ARM/Ch.5/wells_dae.stan
@@ -6,16 +6,15 @@ data {
   vector[N] educ;
 }
 transformed data {
-  vector[N] dist100;         // rescaling
-  vector[N] educ4;
-  dist100 = dist / 100.0;
-  educ4   = educ / 4.0;
+  // rescaling
+  vector[N] dist100 = dist / 100.0;
+  vector[N] educ4 = educ / 4.0;
+  matrix[N,3] x = [dist100', arsenic', educ4']';
 }
 parameters {
-  vector[4] beta;
+  real alpha;
+  vector[3] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * dist100 
-                             + beta[3] * arsenic
-                             + beta[4] * educ4);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_dae_c.stan b/ARM/Ch.5/wells_dae_c.stan
@@ -6,19 +6,16 @@ data {
   vector[N] educ;
 }
 transformed data {
-  vector[N] c_dist100;
-  vector[N] c_arsenic;
-  vector[N] da_inter;
-  vector[N] educ4;
-  c_dist100 = (dist - mean(dist)) / 100.0;
-  c_arsenic = arsenic - mean(arsenic);
-  da_inter  = c_dist100 .* c_arsenic;
-  educ4     = educ / 4.0;
+  vector[N] c_dist100 = (dist - mean(dist)) / 100.0;
+  vector[N] c_arsenic = arsenic - mean(arsenic);
+  vector[N] da_inter = c_dist100 .* c_arsenic;
+  vector[N] educ4 = educ / 4.0;
+  matrix[N,4] x = [c_dist100', c_arsenic', da_inter', educ4']';
 }
 parameters {
-  vector[5] beta;
+  real alpha;
+  vector[4] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * c_dist100 + beta[3] * c_arsenic
-                              + beta[4] * da_inter + beta[5] * educ4);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_dae_inter.stan b/ARM/Ch.5/wells_dae_inter.stan
@@ -6,18 +6,17 @@ data {
   vector[N] educ;
 }
 transformed data {
-  vector[N] dist100;         // rescaling
-  vector[N] educ4;
-  vector[N] inter;           // interaction
-  dist100 = dist / 100.0;
-  educ4   = educ / 4.0;
-  inter   = dist100 .* arsenic;
+  // rescaling
+  vector[N] dist100 = dist / 100.0;
+  vector[N] educ4 = educ / 4.0;
+  // interaction
+  vector[N] inter = dist100 .* arsenic;
+  matrix[N,4] x = [dist100', arsenic', educ4', inter']';
 }
 parameters {
-  vector[5] beta;
+  real alpha;
+  vector[4] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * dist100 
-                             + beta[3] * arsenic + beta[4] * educ4 
-                             + beta[5] * inter);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_dae_inter_c.stan b/ARM/Ch.5/wells_dae_inter_c.stan
@@ -6,24 +6,21 @@ data {
   vector[N] educ;
 }
 transformed data {
-  vector[N] c_dist100;       // centering
-  vector[N] c_arsenic;
-  vector[N] c_educ4;
-  vector[N] da_inter;        // interactions
-  vector[N] de_inter;
-  vector[N] ae_inter;
-  c_dist100 = (dist - mean(dist)) / 100.0;
-  c_arsenic = arsenic - mean(arsenic);
-  c_educ4   = (educ - mean(educ)) / 4.0;
-  da_inter  = c_dist100 .* c_arsenic;
-  de_inter  = c_dist100 .* c_educ4;
-  ae_inter  = c_arsenic .* c_educ4;
+  // centering
+  vector[N] c_dist100 = (dist - mean(dist)) / 100.0;
+  vector[N] c_arsenic = arsenic - mean(arsenic);
+  vector[N] c_educ4 = (educ - mean(educ)) / 4.0;
+  // interactions
+  vector[N] da_inter = c_dist100 .* c_arsenic;
+  vector[N] de_inter = c_dist100 .* c_educ4;
+  vector[N] ae_inter = c_arsenic .* c_educ4;
+  matrix[N,6] x = [c_dist100', c_arsenic', c_educ4',
+                   da_inter', de_inter', ae_inter']';
 }
 parameters {
-  vector[7] beta;
+  real alpha;
+  vector[6] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * c_dist100 + beta[3] * c_arsenic
-                              + beta[4] * c_educ4 + beta[5] * da_inter
-                              + beta[6] * de_inter + beta[7] * ae_inter);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_dist.stan b/ARM/Ch.5/wells_dist.stan
@@ -3,9 +3,13 @@ data {
   int<lower=0,upper=1> switched[N];
   vector[N] dist;
 }
+transformed data {
+  matrix[N,1] x = [dist']';
+}
 parameters {
-  vector[2] beta;
+  real alpha;
+  vector[1] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * dist);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_dist100.stan b/ARM/Ch.5/wells_dist100.stan
@@ -4,12 +4,14 @@ data {
   vector[N] dist;
 }
 transformed data {
-  vector[N] dist100;         // rescaling
-  dist100 = dist / 100.0;   
+  // rescaling
+  vector[N] dist100 = dist / 100.0;   
+  matrix[N,1] x = [dist100']';
 }
 parameters {
-  vector[2] beta;
+  real alpha;
+  vector[1] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * dist100);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_interaction.stan b/ARM/Ch.5/wells_interaction.stan
@@ -5,15 +5,16 @@ data {
   vector[N] arsenic;
 }
 transformed data {
-  vector[N] dist100;         // rescaling
-  vector[N] inter;           // interaction
-  dist100 = dist / 100.0;
-  inter   = dist100 .* arsenic;
+  // rescaling
+  vector[N] dist100 = dist / 100.0;
+  // interaction
+  vector[N] inter = dist100 .* arsenic;
+  matrix[N,3] x = [dist100', arsenic', inter']';
 }
 parameters {
-  vector[4] beta;
+  real alpha;
+  vector[3] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * dist100 
-                             + beta[3] * arsenic + beta[4] * inter);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_interaction_c.stan b/ARM/Ch.5/wells_interaction_c.stan
@@ -5,17 +5,17 @@ data {
   vector[N] arsenic;
 }
 transformed data {
-  vector[N] c_dist100;       // centering
-  vector[N] c_arsenic;
-  vector[N] inter;           // interaction
-  c_dist100 = (dist - mean(dist)) / 100.0;
-  c_arsenic = arsenic - mean(arsenic);
-  inter     = c_dist100 .* c_arsenic;
+  // centering
+  vector[N] c_dist100 = (dist - mean(dist)) / 100.0;
+  vector[N] c_arsenic = arsenic - mean(arsenic);
+  // interaction
+  vector[N] inter = c_dist100 .* c_arsenic;
+  matrix[N,3] x = [c_dist100', c_arsenic', inter']';
 }
 parameters {
-  vector[4] beta;
+  real alpha;
+  vector[3] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * c_dist100 + beta[3] * c_arsenic
-                              + beta[4] * inter);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
diff --git a/ARM/Ch.5/wells_predicted.stan b/ARM/Ch.5/wells_predicted.stan
@@ -6,31 +6,22 @@ data {
   vector[N] educ;
 }
 transformed data {
-  vector[N] c_dist100;
-  vector[N] c_arsenic;
-  vector[N] c_educ4;
-  vector[N] da_inter;
-  vector[N] de_inter;
-  vector[N] ae_inter;
-  c_dist100 = (dist - mean(dist)) / 100.0;
-  c_arsenic = log(arsenic) - mean(log(arsenic));
-  c_educ4   = (educ - mean(educ)) / 4.0;
-  da_inter  = c_dist100 .* c_arsenic;
-  de_inter  = c_dist100 .* c_educ4;
-  ae_inter  = c_arsenic .* c_educ4;
+  vector[N] c_dist100 = (dist - mean(dist)) / 100.0;
+  vector[N] c_arsenic = log(arsenic) - mean(log(arsenic));
+  vector[N] c_educ4 = (educ - mean(educ)) / 4.0;
+  vector[N] da_inter = c_dist100 .* c_arsenic;
+  vector[N] de_inter = c_dist100 .* c_educ4;
+  vector[N] ae_inter = c_arsenic .* c_educ4;
+  matrix[N,6] x = [c_dist100', c_arsenic', c_educ4',
+                   da_inter', de_inter', ae_inter']';
 }
 parameters {
-  vector[7] beta;
+  real alpha;
+  vector[6] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * c_dist100 + beta[3] * c_arsenic
-                              + beta[4] * c_educ4 + beta[5] * da_inter
-                              + beta[6] * de_inter + beta[7] * ae_inter);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
 generated quantities {
-  vector[N] pred;
-  for (i in 1:N)
-    pred[i] = inv_logit(beta[1] + beta[2] * c_dist100[i] + beta[3] * c_arsenic[i]
-                         + beta[4] * c_educ4[i] + beta[5] * da_inter[i]
-                         + beta[6] * de_inter[i] + beta[7] * ae_inter[i]);
+  vector[N] pred = inv_logit(alpha + x * beta);
 }
diff --git a/ARM/Ch.5/wells_predicted_log.stan b/ARM/Ch.5/wells_predicted_log.stan
@@ -6,33 +6,23 @@ data {
   vector[N] educ;
 }
 transformed data {
-  vector[N] c_dist100;
-  vector[N] log_arsenic;
-  vector[N] c_log_arsenic;
-  vector[N] c_educ4;
-  vector[N] da_inter;
-  vector[N] de_inter;
-  vector[N] ae_inter;
-  c_dist100     = (dist - mean(dist)) / 100.0;
-  log_arsenic   = log(arsenic);
-  c_log_arsenic = log_arsenic - mean(log_arsenic);
-  c_educ4       = (educ - mean(educ)) / 4.0;
-  da_inter      = c_dist100 .* c_log_arsenic;
-  de_inter      = c_dist100 .* c_educ4;
-  ae_inter      = c_log_arsenic .* c_educ4;
+  vector[N] c_dist100 = (dist - mean(dist)) / 100.0;
+  vector[N] log_arsenic = log(arsenic);
+  vector[N] c_log_arsenic = log_arsenic - mean(log_arsenic);
+  vector[N] c_educ4 = (educ - mean(educ)) / 4.0;
+  vector[N] da_inter = c_dist100 .* c_log_arsenic;
+  vector[N] de_inter = c_dist100 .* c_educ4;
+  vector[N] ae_inter = c_log_arsenic .* c_educ4;
+  matrix[N,6] x = [c_dist100', c_log_arsenic', c_educ4',
+                   da_inter', de_inter', ae_inter']';
 }
 parameters {
-  vector[7] beta;
+  real alpha;
+  vector[6] beta;
 }
 model {
-  switched ~ bernoulli_logit(beta[1] + beta[2] * c_dist100 + beta[3] * c_log_arsenic
-                              + beta[4] * c_educ4 + beta[5] * da_inter
-                              + beta[6] * de_inter + beta[7] * ae_inter);
+  switched ~ bernoulli_logit_glm(x, alpha, beta);
 }
 generated quantities {
-  vector[N] pred;
-  for (i in 1:N)
-    pred[i] = inv_logit(beta[1] + beta[2] * c_dist100[i] + beta[3] * c_log_arsenic[i]
-                         + beta[4] * c_educ4[i] + beta[5] * da_inter[i]
-                         + beta[6] * de_inter[i] + beta[7] * ae_inter[i]);
+  vector[N] pred = inv_logit(alpha + x * beta);
 }

Original file line number	Diff line number	Diff line change
`@@ -3,9 +3,13 @@ data {`
`3`	`3`	`vector[N] income;`
`4`	`4`	`int<lower=0,upper=1> vote[N];`
`5`	`5`	`}`
	`6`	`+transformed data {`
	`7`	`+ matrix[N,1] x = [income']';`
	`8`	`+}`
`6`	`9`	`parameters {`
`7`		`- vector[2] beta;`
	`10`	`+ real alpha;`
	`11`	`+ vector[1] beta;`
`8`	`12`	`}`
`9`	`13`	`model {`
`10`		`- vote ~ bernoulli_logit(beta[1] + beta[2] * income);`
	`14`	`+ vote ~ bernoulli_logit_glm(x, alpha, beta);`
`11`	`15`	`}`
Original file line number	Diff line number	Diff line change
`@@ -1,11 +1,12 @@`
`1`	`1`	`data {`
`2`	`2`	`int<lower=0> N;`
`3`	`3`	`int<lower=0,upper=1> y[N];`
`4`		`- vector[N] x;`
	`4`	`+ matrix[N,1] x;`
`5`	`5`	`}`
`6`	`6`	`parameters {`
`7`		`- vector[2] beta;`
	`7`	`+ real alpha;`
	`8`	`+ vector[1] beta;`
`8`	`9`	`}`
`9`	`10`	`model {`
`10`		`- y ~ bernoulli_logit(beta[1] + beta[2] * x);`
	`11`	`+ y ~ bernoulli_logit_glm(x, alpha, beta);`
`11`	`12`	`}`
Original file line number	Diff line number	Diff line change
`@@ -5,12 +5,14 @@ data {`
`5`	`5`	`vector[N] arsenic;`
`6`	`6`	`}`
`7`	`7`	`transformed data {`
`8`		`- vector[N] dist100; // rescaling`
`9`		`- dist100 = dist / 100.0;`
	`8`	`+ // rescaling`
	`9`	`+ vector[N] dist100 = dist / 100.0;`
	`10`	`+ matrix[N,2] x = [dist100', arsenic']';`
`10`	`11`	`}`
`11`	`12`	`parameters {`
`12`		`- vector[3] beta;`
	`13`	`+ real alpha;`
	`14`	`+ vector[2] beta;`
`13`	`15`	`}`
`14`	`16`	`model {`
`15`		`- switched ~ bernoulli_logit(beta[1] + beta[2] * dist100 + beta[3] * arsenic);`
	`17`	`+ switched ~ bernoulli_logit_glm(x, alpha, beta);`
`16`	`18`	`}`
Original file line number	Diff line number	Diff line change
`@@ -6,16 +6,15 @@ data {`
`6`	`6`	`vector[N] educ;`
`7`	`7`	`}`
`8`	`8`	`transformed data {`
`9`		`- vector[N] dist100; // rescaling`
`10`		`- vector[N] educ4;`
`11`		`- dist100 = dist / 100.0;`
`12`		`- educ4 = educ / 4.0;`
	`9`	`+ // rescaling`
	`10`	`+ vector[N] dist100 = dist / 100.0;`
	`11`	`+ vector[N] educ4 = educ / 4.0;`
	`12`	`+ matrix[N,3] x = [dist100', arsenic', educ4']';`
`13`	`13`	`}`
`14`	`14`	`parameters {`
`15`		`- vector[4] beta;`
	`15`	`+ real alpha;`
	`16`	`+ vector[3] beta;`
`16`	`17`	`}`
`17`	`18`	`model {`
`18`		`- switched ~ bernoulli_logit(beta[1] + beta[2] * dist100`
`19`		`- + beta[3] * arsenic`
`20`		`- + beta[4] * educ4);`
	`19`	`+ switched ~ bernoulli_logit_glm(x, alpha, beta);`
`21`	`20`	`}`
Original file line number	Diff line number	Diff line change
`@@ -3,9 +3,13 @@ data {`
`3`	`3`	`int<lower=0,upper=1> switched[N];`
`4`	`4`	`vector[N] dist;`
`5`	`5`	`}`
	`6`	`+transformed data {`
	`7`	`+ matrix[N,1] x = [dist']';`
	`8`	`+}`
`6`	`9`	`parameters {`
`7`		`- vector[2] beta;`
	`10`	`+ real alpha;`
	`11`	`+ vector[1] beta;`
`8`	`12`	`}`
`9`	`13`	`model {`
`10`		`- switched ~ bernoulli_logit(beta[1] + beta[2] * dist);`
	`14`	`+ switched ~ bernoulli_logit_glm(x, alpha, beta);`
`11`	`15`	`}`
Original file line number	Diff line number	Diff line change
`@@ -4,12 +4,14 @@ data {`
`4`	`4`	`vector[N] dist;`
`5`	`5`	`}`
`6`	`6`	`transformed data {`
`7`		`- vector[N] dist100; // rescaling`
`8`		`- dist100 = dist / 100.0;`
	`7`	`+ // rescaling`
	`8`	`+ vector[N] dist100 = dist / 100.0;`
	`9`	`+ matrix[N,1] x = [dist100']';`
`9`	`10`	`}`
`10`	`11`	`parameters {`
`11`		`- vector[2] beta;`
	`12`	`+ real alpha;`
	`13`	`+ vector[1] beta;`
`12`	`14`	`}`
`13`	`15`	`model {`
`14`		`- switched ~ bernoulli_logit(beta[1] + beta[2] * dist100);`
	`16`	`+ switched ~ bernoulli_logit_glm(x, alpha, beta);`
`15`	`17`	`}`