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wex: Compute the Exact Observation Weights for the Kalman Filter and Smoother

Computes the exact observation weights for the Kalman filter and smoother, based on the method described in Koopman and Harvey (2003) <www.sciencedirect.com/science/article/pii/S0165188902000611>. The package supports in-depth exploration of state-space models, enabling researchers and practitioners to extract meaningful insights from time series data. This functionality is especially valuable in dynamic factor models, where the computed weights can be used to decompose the contributions of individual variables to the latent factors. See the README file for examples.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: FKF
Published: 2025-05-09
DOI: 10.32614/CRAN.package.wex
Author: Tim Ginker ORCID iD [aut, cre, cph]
Maintainer: Tim Ginker <timginker at gmail.com>
BugReports: https://github.com/timginker/wex/issues
License: MIT + file LICENSE
URL: https://github.com/timginker/wex
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: wex results

Documentation:

Reference manual: wex.pdf

Downloads:

Package source: wex_0.1.0.tar.gz
Windows binaries: r-devel: wex_0.1.0.zip, r-release: wex_0.1.0.zip, r-oldrel: not available
macOS binaries: r-release (arm64): wex_0.1.0.tgz, r-oldrel (arm64): wex_0.1.0.tgz, r-release (x86_64): wex_0.1.0.tgz, r-oldrel (x86_64): wex_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=wex to link to this page.

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.
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