Weighted reservoir sampling using Algorithm A-Chao
A Probablistic Programming Language with a declarative syntax for random variables.
A Probablistic Programming Language with a declarative syntax for random variables.
A library for defining and evaluating random variables using a simple DSL
C-API for Rvs - A library for defining and evaluating random variables using a simple DSL
Parser for Rvs - A library for defining and evaluating random variables using a simple DSL
REPL for Rvs - A library for defining and evaluating random variables using a simple DSL
A high-performance, O(P) data structure for weighted random sampling of binned probabilities, ideal for large-scale simulations.
Tiered randomness for Rust: fast PRNG, process-unique seeds, and OS-backed cryptographic random — plus bounded ranges, strings, tokens, shuffle, sample, and weighted choice. Zero dependencies, MSRV 1.75.
A multi-modal neural network focused on maternal health predictions
Approximate quantiles using histograms with logarithmically sized bins to guarantee worst case absolute relative error.
A Rust library for performing Oaxaca-Blinder decomposition on Polars DataFrames, with support for categorical variables and bootstrapped standard errors.
This gem add Enumerable#weighted_sample_by method.
Produce a weighted random sampling based on the weights calculated from a given block.
Weighted Sampler helps you to pick a random samples from a collection with defined probabilities or weights. You can pass an Array or a Hash with desired probabilities and use Module or Class API to pick samples. Please, see documentation in the repo https://gitlab.com/oleksiy/weighted_sampler