This package is considered a duplicate. The official version of this package is found at:https://gregorkastner.r-universe.dev/factorstochvol

Package: factorstochvol 1.1.2

Gregor Kastner

factorstochvol: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models

Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility models with interweaving <doi:10.1080/10618600.2017.1322091>. Sparsity can be achieved through the usage of Normal-Gamma priors on the factor loading matrix <doi:10.1016/j.jeconom.2018.11.007>.

Authors:Gregor Kastner [aut, cre], Darjus Hosszejni [ctb], Luis Gruber [ctb]

factorstochvol_1.1.2.tar.gz
factorstochvol_1.1.2.zip(r-4.7-x86_64)factorstochvol_1.1.2.zip(r-4.7-arm64)factorstochvol_1.1.2.zip(r-4.6-x86_64)factorstochvol_1.1.2.zip(r-4.6-arm64)
factorstochvol_1.1.2.tar.gz(r-4.7-arm64)factorstochvol_1.1.2.tar.gz(r-4.7-x86_64)factorstochvol_1.1.2.tar.gz(r-4.6-arm64)factorstochvol_1.1.2.tar.gz(r-4.6-x86_64)
factorstochvol_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
factorstochvol/json (API)

# Install 'factorstochvol' in R:

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

Bug tracker:https://github.com/gregorkastner/factorstochvol/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

On CRAN:

openblas cpp

3.38 score 4 stars 1 packages 806 downloads 1 mentions 37 exports 7 dependencies

Last updated from:c8a2f154ae. Checks:10 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	128
linux-devel-x86_64	OK	186
source / vignettes	OK	1464
linux-release-arm64	OK	124
linux-release-x86_64	OK	159
windows-devel-arm64	OK	303
windows-devel-x86_64	OK	404
windows-release-arm64	OK	437
windows-release-x86_64	OK	153
wasm-release	OK	131

Exports:comtimeplot corelement corimageplot cormat corplot cortimeplot covelement covmat covtimeplot evdiag expweightcov facloadcredplot facloaddensplot facloadpairplot facloadpointplot facloadtraceplot findrestrict fsvsample fsvsim ledermann logret logvartimeplot orderident paratraceplot plotalot predcond predcor predcov predh predloglik predloglikWB predprecWB preorder runningcormat runningcovmat signident voltimeplot

Dependencies:coda corrplot GIGrvg lattice Rcpp RcppArmadillo stochvol

Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol

Rendered frompaper.Rtexusingknitr::knitr

Last update: 2026-03-30
Started: 2021-02-09

Citation

Readme and manuals

Help Manual

Help page	Topics
Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models through MCMC	factorstochvol-package factorstochvol
Plot communalities over time.	comtimeplot
Extract "true" model-implied correlations of two series only	corelement
Plot correlation matrices for certain points in time	corimageplot
Generic extraction of correlation matrix	cormat
Extract posterior draws of the model-implied correlation matrix	cormat.fsvdraws
Extract "true" model-implied correlation matrix for several points in time	cormat.fsvsim
Plots pairwise correlations over time	corplot
Plot correlations over time.	cortimeplot covtimeplot
Extract "true" model-implied covariances of two series only	covelement
Generic extraction of covariance matrix	covmat
Extract posterior draws of the model-implied covariance matrix	covmat.fsvdraws
Extract "true" model-implied covariance matrix for several points in time	covmat.fsvsim
Plots posterior draws and posterior means of the eigenvalues of crossprod(facload)	evdiag
Computes the empirical exponentially weighted covariance matrix	expweightcov
Displays bivariate marginal posterior distribution of factor loadings.	facloadcredplot
Density plots of factor loadings draws	facloaddensplot
Displays bivariate marginal posterior distributions of factor loadings.	facloadpairplot
Displays point estimates of the factor loadings posterior.	facloadpointplot
Trace plots of factor loadings draws	facloadtraceplot
Ad-hoc method for (weakly) identifying the factor loadings matrix	findrestrict
Markov Chain Monte Carlo (MCMC) Sampling for the Factor Stochastic Volatility Model.	fsvsample
Simulate data from a factor SV model	fsvsim
Ledermann bound for the number of factors	ledermann
Compute the log returns of a vector-valued time series	logret logret.data.frame logret.matrix
Plot log-variances over time.	logvartimeplot
A posteriori factor order identification	orderident
Trace plots of parameter draws.	paratraceplot paratraceplot.fsvdraws
Default factor SV plot	plot.fsvdraws
Several factor SV plots useful for model diagnostics	plotalot
Predicts means and variances conditionally on the factors	predcond
Predicts correlation matrix	predcor
Predicts covariance matrix	predcov
Predicts factor and idiosyncratic log-volatilities h	predh
Evaluates the predictive log likelihood using the predicted covariance matrix	predloglik
Evaluates the predictive log likelihood using the Woodbury identity	predloglikWB
Predicts precision matrix and its determinant (Woodbury variant)	predprecWB
Ad-hoc methods for determining the order of variables	preorder
Pretty printing of an fsvsdraws object	print.fsvdraws
Extract summary statistics for the posterior correlation matrix which have been stored during sampling	runningcormat
Extract summary statistics for the posterior covariance matrix which have been stored during sampling	runningcovmat
A posteriori sign identification	signident
Plot series-specific volatilities over time.	voltimeplot

Package: factorstochvol 1.1.2

factorstochvol: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)