The package implements the variance identification algorithm for sparse factor analysis described in the paper “Cover It Up! Bipartite Graphs Uncover Identifiability in Sparse Factor Analysis” by Darjus Hosszejni and Sylvia Frühwirth-Schnatter. The paper is available at arXiv.
The package is still under development and the API is subject to change.
For a Matlab implementation, see sparvaride-matlab.
You can install the development version of sparvaride from
GitHub with:
# install.packages("devtools")
devtools::install_github("hdarjus/sparvaride")We can check whether the 3579 counting rule holds for a given binary
matrix delta using the counting_rule_holds function in the
sparvaride package.
library(sparvaride)We define two matrices as above in R:
delta1 <-
matrix(c(1, 0, 0,
0, 1, 0,
0, 0, 1,
1, 1, 1,
1, 0, 1,
1, 0, 1,
1, 0, 1),
nrow = 7, ncol = 3,
byrow = TRUE)
delta2 <-
matrix(c(1, 0, 0,
0, 1, 0,
0, 0, 1,
1, 1, 1,
1, 0, 1,
1, 1, 1,
1, 0, 1),
nrow = 7, ncol = 3,
byrow = TRUE)Then, we call the counting_rule_holds function on these matrices:
counting_rule_holds(delta1)
#> [1] FALSE
counting_rule_holds(delta2)
#> [1] TRUEFor citing our work, please check the citation function in R:
citation("sparvaride")
#>
#> To cite sparvaride in publications use:
#>
#> Hosszejni D, Frühwirth-Schnatter S (2022). "Cover It Up! Bipartite
#> Graphs Uncover Identifiability in Sparse Factor Analysis."
#> doi:10.48550/arXiv.2211.00671
#> <https://doi.org/10.48550/arXiv.2211.00671>, arXiv: 2211.00671.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Unpublished{,
#> title = {Cover It Up! Bipartite Graphs Uncover Identifiability in Sparse Factor Analysis},
#> author = {Darjus Hosszejni and Sylvia Frühwirth-Schnatter},
#> year = {2022},
#> note = {arXiv: 2211.00671},
#> doi = {10.48550/arXiv.2211.00671},
#> }
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