Return Stan code
code()
A character vector with one element per line of code.
#> [1] "data {" #> [2] " int<lower=0> N;" #> [3] " int<lower=0> K;" #> [4] " array[N] int<lower=0, upper=1> y;" #> [5] " matrix[N, K] X;" #> [6] "}" #> [7] "parameters {" #> [8] " real alpha;" #> [9] " vector[K] beta;" #> [10] "}" #> [11] "model {" #> [12] " target += normal_lpdf(alpha | 0, 1);" #> [13] " target += normal_lpdf(beta | 0, 1);" #> [14] " target += bernoulli_logit_glm_lpmf(y | X, alpha, beta);" #> [15] "}" #> [16] "generated quantities {" #> [17] " vector[N] log_lik;" #> [18] " for (n in 1 : N) {" #> [19] " log_lik[n] = bernoulli_logit_lpmf(y[n] | alpha + X[n] * beta);" #> [20] " }" #> [21] "}"#> data { #> int<lower=0> N; #> int<lower=0> K; #> array[N] int<lower=0, upper=1> y; #> matrix[N, K] X; #> } #> parameters { #> real alpha; #> vector[K] beta; #> } #> model { #> target += normal_lpdf(alpha | 0, 1); #> target += normal_lpdf(beta | 0, 1); #> target += bernoulli_logit_glm_lpmf(y | X, alpha, beta); #> } #> generated quantities { #> vector[N] log_lik; #> for (n in 1 : N) { #> log_lik[n] = bernoulli_logit_lpmf(y[n] | alpha + X[n] * beta); #> } #> }# }