DSDRM
0.1.3Distributed Sampling for Dynamic Regression Models
Overview
A toolbox for distributed dynamic regression modeling, parallel estimation, multiple distributed sampling algorithms (Metropolis-Hastings, block bootstrap, adaptive, hypergeometric), sparse matrix optimization, model visualization, prediction and performance evaluation. The philosophy of the package is described in Guo (2025) doi:10.1038/s41598-025-93333-6.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-07-118 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 91%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- 0.1.3Latest2026-07-11 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-11
- Total releases
- 1 / 1 yrs
- License
- Apache License 2.0 OSI
- Minimum R
- ≥ 4.1.0
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("DSDRM")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-09, which the citation names so these numbers can be found later. More on citing and the projects behind them.