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We present a method based on filtering algorithms to estimate the parameters of linear, i.e. the coefficients and the variance of the error term. The proposed algorithms make use of Particle Filters following Ristic, B., Arulampalam, S., Gordon, N. (2004, ISBN: 158053631X) resampling methods. Parameters of logistic regression models are also estimated using an evolutionary particle filter method.
Version: | 0.1.3.1 |
Depends: | R (≥ 3.6.0) |
Imports: | MASS (≥ 7.3-50), stats (≥ 3.5.1) |
Published: | 2023-02-02 |
DOI: | 10.32614/CRAN.package.LMfilteR |
Author: | Christian Llano Robayo [aut, cre], Nazrul Shaikh [aut], Pegu Nilutpal [aut] |
Maintainer: | Christian Llano Robayo <info at cecareus.com> |
BugReports: | https://github.com/ChrissCod/LMfilteR/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | LMfilteR results |
Reference manual: | LMfilteR.pdf |
Package source: | LMfilteR_0.1.3.1.tar.gz |
Windows binaries: | r-devel: LMfilteR_0.1.3.1.zip, r-release: LMfilteR_0.1.3.1.zip, r-oldrel: LMfilteR_0.1.3.1.zip |
macOS binaries: | r-release (arm64): LMfilteR_0.1.3.1.tgz, r-oldrel (arm64): LMfilteR_0.1.3.1.tgz, r-release (x86_64): LMfilteR_0.1.3.1.tgz, r-oldrel (x86_64): LMfilteR_0.1.3.1.tgz |
Old sources: | LMfilteR archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.