Other packages > Find by keyword >

dynr  

Dynamic Models with Regime-Switching
View on CRAN: Click here


Download and install dynr package within the R console
Install from CRAN:
install.packages("dynr")

Install from Github:
library("remotes")
install_github("cran/dynr")

Install by package version:
library("remotes")
install_version("dynr", "0.1.16-114")



Attach the package and use:
library("dynr")
Maintained by
Michael D. Hunter
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-06-09
Latest Update: 2025-09-03
Description:
Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state-space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single-subject time series data or multiple-subject longitudinal data. Ou, Hunter, & Chow (2019) provided a detailed introduction to the interface and more information on the algorithms.
How to cite:
Michael D. Hunter (2016). dynr: Dynamic Models with Regime-Switching. R package version 0.1.16-114, https://cran.r-project.org/web/packages/dynr. Accessed 05 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:34), 0.1.7 (2016-06-09 20:41), 0.1.8-17 (2017-01-09 09:49), 0.1.9-20 (2017-02-24 08:31), 0.1.10-10 (2017-05-21 10:04), 0.1.11-2 (2017-06-17 02:05), 0.1.11-8 (2017-08-21 10:30), 0.1.12-5 (2018-02-08 22:36), 0.1.13-2 (2018-09-15 07:10), 0.1.13-3 (2018-09-16 18:20), 0.1.13-4 (2018-09-24 20:30), 0.1.14-9 (2019-04-02 09:50), 0.1.14-85 (2019-09-13 00:40), 0.1.15-1 (2019-10-05 08:50), 0.1.15-25 (2020-02-11 20:10), 0.1.15-95 (2021-02-20 09:00), 0.1.16-2 (2021-03-16 13:40), 0.1.16-27 (2021-11-18 14:50), 0.1.16-91 (2022-10-17 09:02), 0.1.16-105 (2023-11-28 06:20)
Other packages that cited dynr R package
View dynr citation profile
Other R packages that dynr depends, imports, suggests or enhances
Complete documentation for dynr
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

genie  
Fast, Robust, and Outlier Resistant Hierarchical Clustering
Includes the reference implementation of Genie - a hierarchical clustering algorithm that links two ...
Download / Learn more Package Citations See dependency  
correlation  
Methods for Correlation Analysis
Lightweight package for computing different kinds of correlations, such as partial correlations, Ba ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
cdlTools  
Tools to Download and Work with USDA Cropscape Data
Downloads USDA National Agricultural Statistics Service (NASS) cropscape data for a specified state ...
Download / Learn more Package Citations See dependency  

28,905

R Packages

247,686

Dependencies

76,495

Author Associations

28,906

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA