mirror of
https://github.com/Funkoala14/knowledgebase_law.git
synced 2025-06-09 07:11:53 +08:00
552 lines
13 KiB
JavaScript
552 lines
13 KiB
JavaScript
import {
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__commonJS
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} from "./chunk-2TUXWMP5.js";
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// node_modules/highlight.js/lib/languages/stan.js
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var require_stan = __commonJS({
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"node_modules/highlight.js/lib/languages/stan.js"(exports, module) {
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function stan(hljs) {
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const BLOCKS = [
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"functions",
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"model",
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"data",
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"parameters",
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"quantities",
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"transformed",
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"generated"
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];
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const STATEMENTS = [
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"for",
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"in",
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"if",
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"else",
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"while",
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"break",
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"continue",
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"return"
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];
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const SPECIAL_FUNCTIONS = [
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"print",
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"reject",
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"increment_log_prob|10",
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"integrate_ode|10",
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"integrate_ode_rk45|10",
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"integrate_ode_bdf|10",
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"algebra_solver"
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];
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const VAR_TYPES = [
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"int",
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"real",
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"vector",
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"ordered",
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"positive_ordered",
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"simplex",
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"unit_vector",
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"row_vector",
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"matrix",
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"cholesky_factor_corr|10",
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"cholesky_factor_cov|10",
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"corr_matrix|10",
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"cov_matrix|10",
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"void"
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];
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const FUNCTIONS = [
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"Phi",
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"Phi_approx",
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"abs",
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"acos",
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"acosh",
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"algebra_solver",
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"append_array",
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"append_col",
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"append_row",
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"asin",
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"asinh",
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"atan",
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"atan2",
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"atanh",
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"bernoulli_cdf",
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"bernoulli_lccdf",
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"bernoulli_lcdf",
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"bernoulli_logit_lpmf",
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"bernoulli_logit_rng",
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"bernoulli_lpmf",
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"bernoulli_rng",
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"bessel_first_kind",
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"bessel_second_kind",
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"beta_binomial_cdf",
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"beta_binomial_lccdf",
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"beta_binomial_lcdf",
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"beta_binomial_lpmf",
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"beta_binomial_rng",
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"beta_cdf",
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"beta_lccdf",
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"beta_lcdf",
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"beta_lpdf",
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"beta_rng",
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"binary_log_loss",
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"binomial_cdf",
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"binomial_coefficient_log",
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"binomial_lccdf",
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"binomial_lcdf",
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"binomial_logit_lpmf",
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"binomial_lpmf",
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"binomial_rng",
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"block",
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"categorical_logit_lpmf",
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"categorical_logit_rng",
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"categorical_lpmf",
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"categorical_rng",
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"cauchy_cdf",
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"cauchy_lccdf",
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"cauchy_lcdf",
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"cauchy_lpdf",
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"cauchy_rng",
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"cbrt",
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"ceil",
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"chi_square_cdf",
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"chi_square_lccdf",
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"chi_square_lcdf",
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"chi_square_lpdf",
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"chi_square_rng",
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"cholesky_decompose",
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"choose",
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"col",
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"cols",
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"columns_dot_product",
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"columns_dot_self",
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"cos",
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"cosh",
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"cov_exp_quad",
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"crossprod",
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"csr_extract_u",
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"csr_extract_v",
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"csr_extract_w",
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"csr_matrix_times_vector",
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"csr_to_dense_matrix",
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"cumulative_sum",
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"determinant",
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"diag_matrix",
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"diag_post_multiply",
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"diag_pre_multiply",
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"diagonal",
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"digamma",
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"dims",
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"dirichlet_lpdf",
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"dirichlet_rng",
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"distance",
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"dot_product",
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"dot_self",
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"double_exponential_cdf",
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"double_exponential_lccdf",
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"double_exponential_lcdf",
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"double_exponential_lpdf",
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"double_exponential_rng",
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"e",
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"eigenvalues_sym",
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"eigenvectors_sym",
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"erf",
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"erfc",
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"exp",
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"exp2",
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"exp_mod_normal_cdf",
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"exp_mod_normal_lccdf",
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"exp_mod_normal_lcdf",
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"exp_mod_normal_lpdf",
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"exp_mod_normal_rng",
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"expm1",
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"exponential_cdf",
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"exponential_lccdf",
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"exponential_lcdf",
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"exponential_lpdf",
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"exponential_rng",
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"fabs",
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"falling_factorial",
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"fdim",
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"floor",
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"fma",
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"fmax",
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"fmin",
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"fmod",
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"frechet_cdf",
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"frechet_lccdf",
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"frechet_lcdf",
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"frechet_lpdf",
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"frechet_rng",
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"gamma_cdf",
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"gamma_lccdf",
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"gamma_lcdf",
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"gamma_lpdf",
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"gamma_p",
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"gamma_q",
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"gamma_rng",
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"gaussian_dlm_obs_lpdf",
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"get_lp",
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"gumbel_cdf",
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"gumbel_lccdf",
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"gumbel_lcdf",
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"gumbel_lpdf",
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"gumbel_rng",
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"head",
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"hypergeometric_lpmf",
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"hypergeometric_rng",
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"hypot",
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"inc_beta",
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"int_step",
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"integrate_ode",
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"integrate_ode_bdf",
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"integrate_ode_rk45",
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"inv",
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"inv_Phi",
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"inv_chi_square_cdf",
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"inv_chi_square_lccdf",
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"inv_chi_square_lcdf",
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"inv_chi_square_lpdf",
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"inv_chi_square_rng",
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"inv_cloglog",
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"inv_gamma_cdf",
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"inv_gamma_lccdf",
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"inv_gamma_lcdf",
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"inv_gamma_lpdf",
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"inv_gamma_rng",
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"inv_logit",
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"inv_sqrt",
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"inv_square",
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"inv_wishart_lpdf",
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"inv_wishart_rng",
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"inverse",
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"inverse_spd",
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"is_inf",
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"is_nan",
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"lbeta",
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"lchoose",
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"lgamma",
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"lkj_corr_cholesky_lpdf",
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"lkj_corr_cholesky_rng",
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"lkj_corr_lpdf",
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"lkj_corr_rng",
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"lmgamma",
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"lmultiply",
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"log",
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"log10",
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"log1m",
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"log1m_exp",
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"log1m_inv_logit",
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"log1p",
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"log1p_exp",
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"log2",
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"log_determinant",
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"log_diff_exp",
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"log_falling_factorial",
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"log_inv_logit",
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"log_mix",
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"log_rising_factorial",
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"log_softmax",
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"log_sum_exp",
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"logistic_cdf",
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"logistic_lccdf",
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"logistic_lcdf",
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"logistic_lpdf",
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"logistic_rng",
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"logit",
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"lognormal_cdf",
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"lognormal_lccdf",
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"lognormal_lcdf",
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"lognormal_lpdf",
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"lognormal_rng",
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"machine_precision",
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"matrix_exp",
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"max",
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"mdivide_left_spd",
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"mdivide_left_tri_low",
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"mdivide_right_spd",
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"mdivide_right_tri_low",
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"mean",
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"min",
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"modified_bessel_first_kind",
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"modified_bessel_second_kind",
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"multi_gp_cholesky_lpdf",
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"multi_gp_lpdf",
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"multi_normal_cholesky_lpdf",
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"multi_normal_cholesky_rng",
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"multi_normal_lpdf",
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"multi_normal_prec_lpdf",
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"multi_normal_rng",
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"multi_student_t_lpdf",
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"multi_student_t_rng",
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"multinomial_lpmf",
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"multinomial_rng",
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"multiply_log",
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"multiply_lower_tri_self_transpose",
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"neg_binomial_2_cdf",
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"neg_binomial_2_lccdf",
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"neg_binomial_2_lcdf",
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"neg_binomial_2_log_lpmf",
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"neg_binomial_2_log_rng",
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"neg_binomial_2_lpmf",
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"neg_binomial_2_rng",
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"neg_binomial_cdf",
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"neg_binomial_lccdf",
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"neg_binomial_lcdf",
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"neg_binomial_lpmf",
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"neg_binomial_rng",
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"negative_infinity",
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"normal_cdf",
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"normal_lccdf",
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"normal_lcdf",
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"normal_lpdf",
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"normal_rng",
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"not_a_number",
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"num_elements",
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"ordered_logistic_lpmf",
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"ordered_logistic_rng",
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"owens_t",
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"pareto_cdf",
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"pareto_lccdf",
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"pareto_lcdf",
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"pareto_lpdf",
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"pareto_rng",
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"pareto_type_2_cdf",
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"pareto_type_2_lccdf",
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"pareto_type_2_lcdf",
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"pareto_type_2_lpdf",
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"pareto_type_2_rng",
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"pi",
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"poisson_cdf",
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"poisson_lccdf",
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"poisson_lcdf",
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"poisson_log_lpmf",
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"poisson_log_rng",
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"poisson_lpmf",
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"poisson_rng",
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"positive_infinity",
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"pow",
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"print",
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"prod",
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"qr_Q",
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"qr_R",
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"quad_form",
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"quad_form_diag",
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"quad_form_sym",
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"rank",
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"rayleigh_cdf",
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"rayleigh_lccdf",
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"rayleigh_lcdf",
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"rayleigh_lpdf",
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"rayleigh_rng",
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"reject",
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"rep_array",
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"rep_matrix",
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"rep_row_vector",
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"rep_vector",
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"rising_factorial",
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"round",
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"row",
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"rows",
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"rows_dot_product",
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"rows_dot_self",
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"scaled_inv_chi_square_cdf",
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"scaled_inv_chi_square_lccdf",
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"scaled_inv_chi_square_lcdf",
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"scaled_inv_chi_square_lpdf",
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"scaled_inv_chi_square_rng",
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"sd",
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"segment",
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"sin",
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"singular_values",
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"sinh",
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"size",
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"skew_normal_cdf",
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"skew_normal_lccdf",
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"skew_normal_lcdf",
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"skew_normal_lpdf",
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"skew_normal_rng",
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"softmax",
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"sort_asc",
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"sort_desc",
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"sort_indices_asc",
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"sort_indices_desc",
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"sqrt",
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"sqrt2",
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"square",
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"squared_distance",
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"step",
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"student_t_cdf",
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"student_t_lccdf",
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"student_t_lcdf",
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"student_t_lpdf",
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"student_t_rng",
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"sub_col",
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"sub_row",
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"sum",
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"tail",
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"tan",
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"tanh",
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"target",
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"tcrossprod",
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"tgamma",
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"to_array_1d",
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"to_array_2d",
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"to_matrix",
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"to_row_vector",
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"to_vector",
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"trace",
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"trace_gen_quad_form",
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"trace_quad_form",
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"trigamma",
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"trunc",
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"uniform_cdf",
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"uniform_lccdf",
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"uniform_lcdf",
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"uniform_lpdf",
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"uniform_rng",
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"variance",
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"von_mises_lpdf",
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"von_mises_rng",
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"weibull_cdf",
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"weibull_lccdf",
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"weibull_lcdf",
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"weibull_lpdf",
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"weibull_rng",
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"wiener_lpdf",
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"wishart_lpdf",
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"wishart_rng"
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];
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const DISTRIBUTIONS = [
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"bernoulli",
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"bernoulli_logit",
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"beta",
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"beta_binomial",
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"binomial",
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"binomial_logit",
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"categorical",
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"categorical_logit",
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"cauchy",
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"chi_square",
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"dirichlet",
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"double_exponential",
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"exp_mod_normal",
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"exponential",
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"frechet",
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"gamma",
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"gaussian_dlm_obs",
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"gumbel",
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"hypergeometric",
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"inv_chi_square",
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"inv_gamma",
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"inv_wishart",
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"lkj_corr",
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"lkj_corr_cholesky",
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"logistic",
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"lognormal",
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"multi_gp",
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"multi_gp_cholesky",
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"multi_normal",
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"multi_normal_cholesky",
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"multi_normal_prec",
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"multi_student_t",
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"multinomial",
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"neg_binomial",
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"neg_binomial_2",
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"neg_binomial_2_log",
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"normal",
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"ordered_logistic",
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"pareto",
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"pareto_type_2",
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"poisson",
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"poisson_log",
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"rayleigh",
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"scaled_inv_chi_square",
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"skew_normal",
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"student_t",
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"uniform",
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"von_mises",
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"weibull",
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"wiener",
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"wishart"
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];
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return {
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name: "Stan",
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aliases: ["stanfuncs"],
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keywords: {
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$pattern: hljs.IDENT_RE,
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title: BLOCKS,
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keyword: STATEMENTS.concat(VAR_TYPES).concat(SPECIAL_FUNCTIONS),
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built_in: FUNCTIONS
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},
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contains: [
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hljs.C_LINE_COMMENT_MODE,
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hljs.COMMENT(
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/#/,
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/$/,
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{
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relevance: 0,
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keywords: {
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"meta-keyword": "include"
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}
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}
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),
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hljs.COMMENT(
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/\/\*/,
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/\*\//,
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{
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relevance: 0,
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// highlight doc strings mentioned in Stan reference
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contains: [
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{
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className: "doctag",
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begin: /@(return|param)/
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}
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]
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}
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),
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{
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// hack: in range constraints, lower must follow "<"
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begin: /<\s*lower\s*=/,
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keywords: "lower"
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},
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{
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// hack: in range constraints, upper must follow either , or <
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// <lower = ..., upper = ...> or <upper = ...>
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begin: /[<,]\s*upper\s*=/,
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keywords: "upper"
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},
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{
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className: "keyword",
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begin: /\btarget\s*\+=/,
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relevance: 10
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},
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{
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begin: "~\\s*(" + hljs.IDENT_RE + ")\\s*\\(",
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keywords: DISTRIBUTIONS
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},
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{
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className: "number",
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variants: [
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{
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begin: /\b\d+(?:\.\d*)?(?:[eE][+-]?\d+)?/
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},
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{
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begin: /\.\d+(?:[eE][+-]?\d+)?\b/
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}
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],
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relevance: 0
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},
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{
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className: "string",
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begin: '"',
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end: '"',
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relevance: 0
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}
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]
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};
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}
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module.exports = stan;
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}
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});
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export {
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require_stan
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};
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//# sourceMappingURL=chunk-SLBUMATW.js.map
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