Statistics and sampling

Streaming statistics, selection, random engines and Monte Carlo sampling. The concepts are on the Concepts page.

Running statistics <stats/stats.hpp>

running_stats – basic_running_stats – histogram – basic_histogram – autocorr_time

Probability vectors <stats/probability.hpp>

clip_and_normalize_nonnegative – weighted_sum

Selection <stats/selection.hpp>

argmax – argsort – smallest_indices – filter – group_by

Random engines <stochastic/rng.hpp>

rng – rng64 – markov::make_rng – markov::make_seeded_rng

Categorical sampling <stochastic/categorical.hpp>

categorical_sampler – sample_categorical

Random probes <stochastic/probe.hpp>

rademacher_probe – gaussian_probe – hutchinson_row_mean_square

Metropolis and umbrella sampling <stochastic/mcmc.hpp>

markov::metropolis_stats – markov::umbrella_stats – markov::umbrella_window

Sweeps <stochastic/detail/mcmc_impl.hpp>

markov::metropolis_sweep – markov::metropolis_sweep_prob – markov::umbrella_sweep – markov::umbrella_sweep_prob

Boltzmann tables <stochastic/boltzmann_table.hpp>

markov::boltzmann_accept – markov::make_boltzmann_table