From 873dfe7d479edd13e1901df9554b6e7e5af03e45 Mon Sep 17 00:00:00 2001 From: Andrew Johnson Date: Sat, 2 Sep 2023 01:43:06 +0300 Subject: [PATCH] Update deprecated syntax --- DESCRIPTION | 6 ++-- inst/stan/distribution_covariate_model.stan | 40 ++++++++++----------- 2 files changed, 23 insertions(+), 23 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 2cef3cb..d7085b0 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -30,7 +30,7 @@ Imports: methods, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), - rstan (>= 2.18.1), + rstan (>= 2.26.0), rstantools (>= 2.2.0), scales, tidybayes, @@ -40,8 +40,8 @@ LinkingTo: Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), - rstan (>= 2.18.1), - StanHeaders (>= 2.18.0) + rstan (>= 2.26.0), + StanHeaders (>= 2.26.0) SystemRequirements: GNU make Suggests: bayesplot, diff --git a/inst/stan/distribution_covariate_model.stan b/inst/stan/distribution_covariate_model.stan index b5e28ea..a8e3ead 100644 --- a/inst/stan/distribution_covariate_model.stan +++ b/inst/stan/distribution_covariate_model.stan @@ -85,25 +85,25 @@ data { // delay distribution for time of kit use to reporting int N_psi; - real psi[N_psi]; + array[N_psi] real psi; // vector (time, HSDA) of regions (coded 1 to N_region) - int regions[N_distributed]; + array[N_distributed] int regions; // vector (time, HSDA) of regions (coded 1 to N_t) - int times[N_distributed]; + array[N_distributed] int times; // vector (time, HSDA) of orders - int Orders[N]; + array[N] int Orders; // create 2D version of Orders data - int Orders2D[N_region,N_t]; + array[N_region,N_t] int Orders2D; // vector (time, HSDA) reported as distributed - int Reported_Distributed[N_distributed]; + array[N_distributed] int Reported_Distributed; // vector (time, HSDA) reported as used - int Reported_Used[N_distributed]; + array[N_distributed] int Reported_Used; //hyper-priors real mu0_sigma; @@ -122,9 +122,9 @@ transformed data{ // calculate discretized delay distribution - trunc_pmf = gamma_cdf(max_delays + 1, alpha, beta) - gamma_cdf(1, alpha, beta); + trunc_pmf = gamma_cdf(max_delays + 1 | alpha, beta) - gamma_cdf(1 | alpha, beta); for (i in 1:max_delays){ - distribute_pmf[i] = (gamma_cdf(i + 1, alpha, beta) - gamma_cdf(i, alpha, beta)) / + distribute_pmf[i] = (gamma_cdf(i + 1 | alpha, beta) - gamma_cdf(i | alpha, beta)) / trunc_pmf; } // reverse delay distribution @@ -141,13 +141,13 @@ transformed data{ // The parameters accepted by the model. parameters { - real logp[N_distributed]; + array[N_distributed] real logp; real sigma; real zeta; real mu0; - real c[N_region]; // region covariates - real ct[N_t]; // time covariates + array[N_region] real c; // region covariates + array[N_t] real ct; // time covariates @@ -155,7 +155,7 @@ parameters { //transformed parameters transformed parameters{ - real p[N_distributed]; + array[N_distributed] real p; p = inv_logit(logp); } @@ -196,17 +196,17 @@ model { // simulated quantities based on model generated quantities { - int sim_used[N]; + array[N] int sim_used; //vector[N] sim_used; - int Distributed[N]; - int Distributed2D[N_region,N_t]; - real sim_p[N]; - real sim_p2D[N_region,N_t]; + array[N] int Distributed; + array[N_region,N_t] int Distributed2D; + array[N] real sim_p; + array[N_region,N_t] real sim_p2D; vector[N] sim_actual_used; - int region_distributed[N_t]; - int convolve_region_distributed[N_t]; + array[N_t] int region_distributed; + array[N_t] int convolve_region_distributed; for(i in 1:N_region){