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Merge branch 'develop' into hyper-1f0
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‎.github/PULL_REQUEST_TEMPLATE.md

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@@ -26,8 +26,6 @@ Replace this text with a short note on what will change if this pull request is
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## Checklist
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- [ ] Math issue #(issue number)
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- [ ] Copyright holder: (fill in copyright holder information)
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The copyright holder is typically you or your assignee, such as a university or company. By submitting this pull request, the copyright holder is agreeing to the license the submitted work under the following licenses:

‎stan/math/prim/meta/ref_type.hpp

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@@ -2,6 +2,7 @@
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#define STAN_MATH_PRIM_META_REF_TYPE_HPP
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#include <stan/math/prim/fun/Eigen.hpp>
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#include <stan/math/prim/meta/is_constant.hpp>
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#include <stan/math/prim/meta/is_eigen.hpp>
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#include <stan/math/prim/meta/is_arena_matrix.hpp>
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#include <stan/math/prim/meta/is_vector.hpp>
@@ -56,6 +57,10 @@ using ref_type_t = typename ref_type_if<true, T>::type;
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template <bool Condition, typename T>
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using ref_type_if_t = typename ref_type_if<Condition, T>::type;
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template <typename T>
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using ref_type_if_not_constant_t =
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typename ref_type_if<!is_constant<T>::value, T>::type;
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} // namespace stan
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#endif

‎stan/math/prim/prob/bernoulli_logit_glm_lpmf.hpp

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@@ -65,9 +65,9 @@ return_type_t<T_x, T_alpha, T_beta> bernoulli_logit_glm_lpmf(
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using T_xbeta_tmp =
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typename std::conditional_t<T_x_rows == 1, T_xbeta_partials,
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Array<T_xbeta_partials, Dynamic, 1>>;
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using T_x_ref = ref_type_if_t<!is_constant<T_x>::value, T_x>;
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using T_alpha_ref = ref_type_if_t<!is_constant<T_alpha>::value, T_alpha>;
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using T_beta_ref = ref_type_if_t<!is_constant<T_beta>::value, T_beta>;
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using T_x_ref = ref_type_if_not_constant_t<T_x>;
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using T_alpha_ref = ref_type_if_not_constant_t<T_alpha>;
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using T_beta_ref = ref_type_if_not_constant_t<T_beta>;
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const size_t N_instances = T_x_rows == 1 ? stan::math::size(y) : x.rows();
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const size_t N_attributes = x.cols();

‎stan/math/prim/prob/bernoulli_logit_lpmf.hpp

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@@ -37,8 +37,8 @@ return_type_t<T_prob> bernoulli_logit_lpmf(const T_n& n, const T_prob& theta) {
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using T_partials_return = partials_return_t<T_n, T_prob>;
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using T_partials_array = Eigen::Array<T_partials_return, Eigen::Dynamic, 1>;
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using std::exp;
40-
using T_n_ref = ref_type_if_t<!is_constant<T_n>::value, T_n>;
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using T_theta_ref = ref_type_if_t<!is_constant<T_prob>::value, T_prob>;
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using T_n_ref = ref_type_if_not_constant_t<T_n>;
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using T_theta_ref = ref_type_if_not_constant_t<T_prob>;
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static const char* function = "bernoulli_logit_lpmf";
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check_consistent_sizes(function, "Random variable", n,
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"Probability parameter", theta);

‎stan/math/prim/prob/beta_lpdf.hpp

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@@ -47,11 +47,9 @@ template <bool propto, typename T_y, typename T_scale_succ,
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return_type_t<T_y, T_scale_succ, T_scale_fail> beta_lpdf(
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const T_y& y, const T_scale_succ& alpha, const T_scale_fail& beta) {
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using T_partials_return = partials_return_t<T_y, T_scale_succ, T_scale_fail>;
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using T_y_ref = ref_type_if_t<!is_constant<T_y>::value, T_y>;
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using T_alpha_ref
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= ref_type_if_t<!is_constant<T_scale_succ>::value, T_scale_succ>;
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using T_beta_ref
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= ref_type_if_t<!is_constant<T_scale_fail>::value, T_scale_fail>;
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using T_y_ref = ref_type_if_not_constant_t<T_y>;
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using T_alpha_ref = ref_type_if_not_constant_t<T_scale_succ>;
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using T_beta_ref = ref_type_if_not_constant_t<T_scale_fail>;
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static const char* function = "beta_lpdf";
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check_consistent_sizes(function, "Random variable", y,
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"First shape parameter", alpha,

‎stan/math/prim/prob/beta_proportion_lpdf.hpp

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@@ -53,9 +53,9 @@ return_type_t<T_y, T_loc, T_prec> beta_proportion_lpdf(const T_y& y,
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const T_prec& kappa) {
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using T_partials_return = partials_return_t<T_y, T_loc, T_prec>;
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using std::log;
56-
using T_y_ref = ref_type_if_t<!is_constant<T_y>::value, T_y>;
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using T_mu_ref = ref_type_if_t<!is_constant<T_loc>::value, T_loc>;
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using T_kappa_ref = ref_type_if_t<!is_constant<T_prec>::value, T_prec>;
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using T_y_ref = ref_type_if_not_constant_t<T_y>;
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using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
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using T_kappa_ref = ref_type_if_not_constant_t<T_prec>;
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static const char* function = "beta_proportion_lpdf";
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check_consistent_sizes(function, "Random variable", y, "Location parameter",
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mu, "Precision parameter", kappa);

‎stan/math/prim/prob/binomial_logit_lpmf.hpp

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@@ -37,9 +37,9 @@ template <bool propto, typename T_n, typename T_N, typename T_prob,
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return_type_t<T_prob> binomial_logit_lpmf(const T_n& n, const T_N& N,
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const T_prob& alpha) {
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using T_partials_return = partials_return_t<T_n, T_N, T_prob>;
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using T_n_ref = ref_type_if_t<!is_constant<T_n>::value, T_n>;
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using T_N_ref = ref_type_if_t<!is_constant<T_N>::value, T_N>;
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using T_alpha_ref = ref_type_if_t<!is_constant<T_prob>::value, T_prob>;
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using T_n_ref = ref_type_if_not_constant_t<T_n>;
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using T_N_ref = ref_type_if_not_constant_t<T_N>;
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using T_alpha_ref = ref_type_if_not_constant_t<T_prob>;
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static const char* function = "binomial_logit_lpmf";
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check_consistent_sizes(function, "Successes variable", n,
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"Population size parameter", N,

‎stan/math/prim/prob/categorical_logit_glm_lpmf.hpp

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@@ -54,9 +54,9 @@ return_type_t<T_x, T_alpha, T_beta> categorical_logit_glm_lpmf(
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using std::isfinite;
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using std::log;
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using T_y_ref = ref_type_t<T_y>;
57-
using T_x_ref = ref_type_if_t<!is_constant<T_x>::value, T_x>;
58-
using T_alpha_ref = ref_type_if_t<!is_constant<T_alpha>::value, T_alpha>;
59-
using T_beta_ref = ref_type_if_t<!is_constant<T_beta>::value, T_beta>;
57+
using T_x_ref = ref_type_if_not_constant_t<T_x>;
58+
using T_alpha_ref = ref_type_if_not_constant_t<T_alpha>;
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using T_beta_ref = ref_type_if_not_constant_t<T_beta>;
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using T_beta_partials = partials_type_t<scalar_type_t<T_beta>>;
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constexpr int T_x_rows = T_x::RowsAtCompileTime;
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‎stan/math/prim/prob/cauchy_lpdf.hpp

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@@ -44,9 +44,9 @@ return_type_t<T_y, T_loc, T_scale> cauchy_lpdf(const T_y& y, const T_loc& mu,
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const T_scale& sigma) {
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using T_partials_return = partials_return_t<T_y, T_loc, T_scale>;
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using std::log;
47-
using T_y_ref = ref_type_if_t<!is_constant<T_y>::value, T_y>;
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using T_mu_ref = ref_type_if_t<!is_constant<T_loc>::value, T_loc>;
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using T_sigma_ref = ref_type_if_t<!is_constant<T_scale>::value, T_scale>;
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using T_y_ref = ref_type_if_not_constant_t<T_y>;
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using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
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using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
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static const char* function = "cauchy_lpdf";
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check_consistent_sizes(function, "Random variable", y, "Location parameter",
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mu, "Scale parameter", sigma);

‎stan/math/prim/prob/double_exponential_cdf.hpp

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@@ -45,9 +45,9 @@ return_type_t<T_y, T_loc, T_scale> double_exponential_cdf(
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|| is_vector<T_scale>::value,
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T_partials_array, T_partials_return>;
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using std::exp;
48-
using T_y_ref = ref_type_if_t<!is_constant<T_y>::value, T_y>;
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using T_mu_ref = ref_type_if_t<!is_constant<T_loc>::value, T_loc>;
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using T_sigma_ref = ref_type_if_t<!is_constant<T_scale>::value, T_scale>;
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using T_y_ref = ref_type_if_not_constant_t<T_y>;
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using T_mu_ref = ref_type_if_not_constant_t<T_loc>;
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using T_sigma_ref = ref_type_if_not_constant_t<T_scale>;
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static const char* function = "double_exponential_cdf";
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T_y_ref y_ref = y;
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T_mu_ref mu_ref = mu;

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