marvellous122/R-to-JS: 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.

Getting started

Package details

Maintainer
LicenseGPL-3
Version2.0.6.1
URL https://kingaa.github.io/pomp/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("marvellous122/R-to-JS")
marvellous122/R-to-JS documentation built on May 20, 2019, 9:55 a.m.