R-universe search: topic:markov-model

Showing 5 of total 5 results (show query)

spedygiorgio

markovchain:Easy Handling Discrete Time Markov Chains

Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>. Some functions for continuous times Markov chains depend on the suggested ctmcd package.

Maintained by Giorgio Alfredo Spedicato. Last updated 5 months ago.

ctmc dtmc markov-chain markov-model r-programming rcpp openblas cpp

104 stars 12.78 score 712 scripts 4 dependents

kingaa

pomp:Statistical Inference for Partially Observed Markov Processes

Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.

Maintained by Aaron A. King. Last updated 13 days ago.

abc b-spline differential-equations dynamical-systems iterated-filtering likelihood likelihood-free markov-chain-monte-carlo markov-model mathematical-modelling measurement-error particle-filter sequential-monte-carlo simulation-based-inference sobol-sequence state-space statistical-inference stochastic-processes time-series openblas

114 stars 11.74 score 1.3k scripts 4 dependents

eheinzen

elo:Ranking Teams by Elo Rating and Comparable Methods

A flexible framework for calculating Elo ratings and resulting rankings of any two-team-per-matchup system (chess, sports leagues, 'Go', etc.). This implementation is capable of evaluating a variety of matchups, Elo rating updates, and win probabilities, all based on the basic Elo rating system. It also includes methods to benchmark performance, including logistic regression and Markov chain models.

Maintained by Ethan Heinzen. Last updated 1 years ago.

elo elo-rating logistic-regression markov-chain markov-model ranking sports-analytics cpp

37 stars 7.05 score 153 scripts

fabrice-rossi

mixvlmc:Variable Length Markov Chains with Covariates

Estimates Variable Length Markov Chains (VLMC) models and VLMC with covariates models from discrete sequences. Supports model selection via information criteria and simulation of new sequences from an estimated model. See Bühlmann, P. and Wyner, A. J. (1999) <doi:10.1214/aos/1018031204> for VLMC and Zanin Zambom, A., Kim, S. and Lopes Garcia, N. (2022) <doi:10.1111/jtsa.12615> for VLMC with covariates.

Maintained by Fabrice Rossi. Last updated 11 months ago.

machine-learning markov-chain markov-model statistics time-series cpp

2 stars 5.86 score 20 scripts

sonsoleslp

tna:Transition Network Analysis (TNA)

Provides tools for performing Transition Network Analysis (TNA) to study relational dynamics, including functions for building and plotting TNA models, calculating centrality measures, and identifying dominant events and patterns. TNA statistical techniques (e.g., bootstrapping and permutation tests) ensure the reliability of observed insights and confirm that identified dynamics are meaningful. See (Saqr et al., 2025) <doi:10.1145/3706468.3706513> for more details on TNA.

Maintained by Sonsoles López-Pernas. Last updated 6 hours ago.

educational-data-mining learning-analytics markov-model temporal-analysis

4 stars 5.75 score 5 scripts