Package: sparvaride 1.0.0

sparvaride: Variance Identification in Sparse Factor Analysis

This is an implementation of the algorithm described in Section 3 of Hosszejni and Frühwirth-Schnatter (2026) <doi:10.1016/j.jmva.2025.105536>. The algorithm is used to verify that the counting rule CR(r,1) holds for the sparsity pattern of the transpose of a factor loading matrix. As detailed in Section 2 of the same paper, if CR(r,1) holds, then the idiosyncratic variances are generically identified. If CR(r,1) does not hold, then we do not know whether the idiosyncratic variances are identified or not.

Authors:Darjus Hosszejni [aut, cre], Sylvia Frühwirth-Schnatter [ths]

sparvaride_1.0.0.tar.gz
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sparvaride_1.0.0.tgz(r-4.6-x86_64)sparvaride_1.0.0.tgz(r-4.6-arm64)sparvaride_1.0.0.tgz(r-4.5-x86_64)sparvaride_1.0.0.tgz(r-4.5-arm64)
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sparvaride_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sparvaride/json (API)

# Install 'sparvaride' in R:

install.packages('sparvaride', repos = c('https://hdarjus.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hdarjus/sparvaride/issues

Pkgdown/docs site:https://hdarjus.github.io

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

econometrics factor-analysis latent-factors parameter-identification cpp

3.70 score 1 stars 10 scripts 194 downloads 1 exports 2 dependencies

Last updated from:55c91d962d. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	128
linux-devel-x86_64	OK	138
source / vignettes	OK	193
linux-release-arm64	OK	129
linux-release-x86_64	OK	138
macos-release-arm64	OK	173
macos-release-x86_64	OK	450
macos-oldrel-arm64	OK	159
macos-oldrel-x86_64	OK	333
windows-devel	OK	264
windows-release	OK	103
windows-oldrel	OK	118
wasm-release	OK	101