diff --git a/inst/stan/NB.stan b/inst/stan/NB.stan index 39ccde7..6d4b038 100644 --- a/inst/stan/NB.stan +++ b/inst/stan/NB.stan @@ -17,7 +17,7 @@ data { int N; // Number of observations int K; // Number of covariates - int y[N]; // Outcome variable + array[N] int y; // Outcome variable matrix[N, K] X; // Model matrix vector[N] treat; // Treatment indicator real tau_mean; // Prior mean for treatment effect diff --git a/inst/stan/hurdlelognormal.stan b/inst/stan/hurdlelognormal.stan index e1650f8..0552762 100644 --- a/inst/stan/hurdlelognormal.stan +++ b/inst/stan/hurdlelognormal.stan @@ -17,7 +17,7 @@ data { // Data dimensions int N; // Number of observations - int treatment[N]; // Treatment indicator (0 or 1) + array[N] int treatment; // Treatment indicator (0 or 1) int K; // Number of predictors (columns in X) // Data matrix[N, K] X; // Design matrix @@ -119,8 +119,8 @@ generated quantities { real ATE; real tau_prob_zero; - int y0_zero[N]; - int y1_zero[N]; + array[N] int y0_zero; + array[N] int y1_zero; for (n in 1:N) { // Linear predictors for both treatment and control diff --git a/inst/stan/logit.stan b/inst/stan/logit.stan index 7de7957..52bae40 100644 --- a/inst/stan/logit.stan +++ b/inst/stan/logit.stan @@ -16,7 +16,7 @@ data { int N; // Number of observations - int y[N]; // Outcome (binary 0 or 1) + array[N] int y; // Outcome (binary 0 or 1) int K; // Number of covariates matrix[N, K] X; // Model matrix (contains predictor values) real mean_alpha; diff --git a/inst/stan/metaanalysisnox.stan b/inst/stan/metaanalysisnox.stan index 7c79c41..2d4e3f5 100644 --- a/inst/stan/metaanalysisnox.stan +++ b/inst/stan/metaanalysisnox.stan @@ -21,8 +21,8 @@ data { int J; // number of studies - real y[J]; // estimated lift - real sigma[J]; // standard error of lift estimates + array[J] real y; // estimated lift + array[J] real sigma; // standard error of lift estimates int run_estimation; real sd_mu; real mean_mu;