| add(size_t chain, std::vector< double > theta) | stan::mcmc::chains< RNG > | inline |
| apply_kept_samples(size_t k, size_t n, F &f) | stan::mcmc::chains< RNG > | inline |
| apply_kept_samples(size_t n, F &f) | stan::mcmc::chains< RNG > | inline |
| autocorrelation(const size_t k, const size_t n, std::vector< double > &ac) | stan::mcmc::chains< RNG > | inline |
| autocovariance(const size_t k, const size_t n, std::vector< double > &acov) | stan::mcmc::chains< RNG > | inline |
| central_interval(size_t k, size_t n, double prob) | stan::mcmc::chains< RNG > | inline |
| central_interval(size_t n, double prob) | stan::mcmc::chains< RNG > | inline |
| chains(const size_t num_chains, const std::vector< std::string > &names, const std::vector< std::vector< size_t > > &dimss) | stan::mcmc::chains< RNG > | inline |
| correlation(size_t k, size_t n1, size_t n2) | stan::mcmc::chains< RNG > | inline |
| correlation(size_t n1, size_t n2) | stan::mcmc::chains< RNG > | inline |
| covariance(size_t k, size_t n1, size_t n2) | stan::mcmc::chains< RNG > | inline |
| covariance(size_t n1, size_t n2) | stan::mcmc::chains< RNG > | inline |
| effective_sample_size(size_t n) | stan::mcmc::chains< RNG > | inline |
| get_kept_samples(size_t k, size_t n, std::vector< double > &samples) | stan::mcmc::chains< RNG > | inline |
| get_kept_samples_permuted(size_t n, std::vector< double > &samples) | stan::mcmc::chains< RNG > | inline |
| get_samples(size_t n, std::vector< double > &samples) | stan::mcmc::chains< RNG > | inline |
| get_samples(size_t k, size_t n, std::vector< double > &samples) | stan::mcmc::chains< RNG > | inline |
| get_total_param_index(size_t j, const std::vector< size_t > &idxs) | stan::mcmc::chains< RNG > | inline |
| get_warmup_samples(size_t n, std::vector< double > &samples) | stan::mcmc::chains< RNG > | inline |
| get_warmup_samples(size_t k, size_t n, std::vector< double > &samples) | stan::mcmc::chains< RNG > | inline |
| mean(size_t k, size_t n) | stan::mcmc::chains< RNG > | inline |
| mean(size_t n) | stan::mcmc::chains< RNG > | inline |
| num_chains() | stan::mcmc::chains< RNG > | inline |
| num_kept_samples(size_t k) | stan::mcmc::chains< RNG > | inline |
| num_kept_samples() | stan::mcmc::chains< RNG > | inline |
| num_param_names() | stan::mcmc::chains< RNG > | inline |
| num_params() | stan::mcmc::chains< RNG > | inline |
| num_samples() | stan::mcmc::chains< RNG > | inline |
| num_samples(size_t k) | stan::mcmc::chains< RNG > | inline |
| num_warmup_samples(size_t k) | stan::mcmc::chains< RNG > | inline |
| num_warmup_samples() | stan::mcmc::chains< RNG > | inline |
| param_dims(size_t j) | stan::mcmc::chains< RNG > | inline |
| param_dimss() | stan::mcmc::chains< RNG > | inline |
| param_name(size_t j) | stan::mcmc::chains< RNG > | inline |
| param_name_to_index(const std::string &name) | stan::mcmc::chains< RNG > | inline |
| param_names() | stan::mcmc::chains< RNG > | inline |
| param_size(size_t j) | stan::mcmc::chains< RNG > | inline |
| param_sizes() | stan::mcmc::chains< RNG > | inline |
| param_start(size_t j) | stan::mcmc::chains< RNG > | inline |
| param_starts() | stan::mcmc::chains< RNG > | inline |
| quantile(size_t k, size_t n, double prob) | stan::mcmc::chains< RNG > | inline |
| quantile(size_t n, double prob) | stan::mcmc::chains< RNG > | inline |
| quantiles(size_t k, size_t n, const std::vector< double > &probs, std::vector< double > &quantiles) | stan::mcmc::chains< RNG > | inline |
| quantiles(size_t n, const std::vector< double > &probs, std::vector< double > &quantiles) | stan::mcmc::chains< RNG > | inline |
| sd(size_t k, size_t n) | stan::mcmc::chains< RNG > | inline |
| sd(size_t n) | stan::mcmc::chains< RNG > | inline |
| set_warmup(size_t warmup_iterations) | stan::mcmc::chains< RNG > | inline |
| split_potential_scale_reduction(size_t n) | stan::mcmc::chains< RNG > | inline |
| variance(size_t k, size_t n) | stan::mcmc::chains< RNG > | inline |
| variance(size_t n) | stan::mcmc::chains< RNG > | inline |
| warmup() | stan::mcmc::chains< RNG > | inline |
