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.
Last updated 21 days ago
abcb-splinedifferential-equationsdynamical-systemsiterated-filteringlikelihoodlikelihood-freemarkov-chain-monte-carlomarkov-modelmathematical-modellingmeasurement-errorparticle-filtersequential-monte-carlosimulation-based-inferencesobol-sequencestate-spacestatistical-inferencestochastic-processestime-seriesopenblas
11.63 score 114 stars 4 dependents 1.3k scripts 2.1k downloadssubplex - Unconstrained Optimization using the Subplex Algorithm
The subplex algorithm for unconstrained optimization, developed by Tom Rowan.
Last updated 3 months ago
numerical-optimizationoptimizationfortranopenblas
8.05 score 10 stars 45 dependents 55 scripts 4.4k downloadsouch - Ornstein-Uhlenbeck Models for Phylogenetic Comparative Hypotheses
Fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic tree.
Last updated 3 months ago
adaptive-regimebrownian-motionornstein-uhlenbeckornstein-uhlenbeck-modelsouchphylogenetic-comparative-hypothesesphylogenetic-comparative-methodsphylogenetic-datareact
6.93 score 15 stars 4 dependents 68 scripts 631 downloads