Package: factorstochvol 1.1.0

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]

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factorstochvol.pdf |factorstochvol.html✨
factorstochvol/json (API)
NEWS

# Install 'factorstochvol' in R:
install.packages('factorstochvol', repos = c('https://gregorkastner.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

37 exports 6 stars 1.98 score 7 dependencies 1 dependents 1 mentions 15 scripts 586 downloads

Last updated 10 months agofrom:b467797a43. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 08 2024
R-4.5-win-x86_64WARNINGSep 08 2024
R-4.5-linux-x86_64WARNINGSep 08 2024
R-4.4-win-x86_64WARNINGSep 08 2024
R-4.4-mac-x86_64WARNINGSep 08 2024
R-4.4-mac-aarch64WARNINGSep 08 2024
R-4.3-win-x86_64WARNINGSep 08 2024
R-4.3-mac-x86_64WARNINGSep 08 2024
R-4.3-mac-aarch64WARNINGSep 08 2024

Exports:comtimeplotcorelementcorimageplotcormatcorplotcortimeplotcovelementcovmatcovtimeplotevdiagexpweightcovfacloadcredplotfacloaddensplotfacloadpairplotfacloadpointplotfacloadtraceplotfindrestrictfsvsamplefsvsimledermannlogretlogvartimeplotorderidentparatraceplotplotalotpredcondpredcorpredcovpredhpredloglikpredloglikWBpredprecWBpreorderrunningcormatrunningcovmatsignidentvoltimeplot

Dependencies:codacorrplotGIGrvglatticeRcppRcppArmadillostochvol

Readme and manuals

Help Manual

Help pageTopics
Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models through MCMCfactorstochvol-package
Plot communalities over time.comtimeplot
Extract "true" model-implied correlations of two series onlycorelement
Plot correlation matrices for certain points in timecorimageplot
Generic extraction of correlation matrixcormat
Extract posterior draws of the model-implied correlation matrixcormat.fsvdraws
Extract "true" model-implied correlation matrix for several points in timecormat.fsvsim
Plots pairwise correlations over timecorplot
Plot correlations over time.cortimeplot covtimeplot
Extract "true" model-implied covariances of two series onlycovelement
Generic extraction of covariance matrixcovmat
Extract posterior draws of the model-implied covariance matrixcovmat.fsvdraws
Extract "true" model-implied covariance matrix for several points in timecovmat.fsvsim
Plots posterior draws and posterior means of the eigenvalues of crossprod(facload)evdiag
Computes the empirical exponentially weighted covariance matrixexpweightcov
Displays bivariate marginal posterior distribution of factor loadings.facloadcredplot
Density plots of factor loadings drawsfacloaddensplot
Displays bivariate marginal posterior distributions of factor loadings.facloadpairplot
Displays point estimates of the factor loadings posterior.facloadpointplot
Trace plots of factor loadings drawsfacloadtraceplot
Ad-hoc method for (weakly) identifying the factor loadings matrixfindrestrict
Markov Chain Monte Carlo (MCMC) Sampling for the Factor Stochastic Volatility Model.fsvsample
Simulate data from a factor SV modelfsvsim
Ledermann bound for the number of factorsledermann
Compute the log returns of a vector-valued time serieslogret logret.data.frame logret.matrix
Plot log-variances over time.logvartimeplot
A posteriori factor order identificationorderident
Trace plots of parameter draws.paratraceplot paratraceplot.fsvdraws
Default factor SV plotplot.fsvdraws
Several factor SV plots useful for model diagnosticsplotalot
Predicts means and variances conditionally on the factorspredcond
Predicts correlation matrixpredcor
Predicts covariance matrixpredcov
Predicts factor and idiosyncratic log-volatilities hpredh
Evaluates the predictive log likelihood using the predicted covariance matrixpredloglik
Evaluates the predictive log likelihood using the Woodbury identitypredloglikWB
Predicts precision matrix and its determinant (Woodbury variant)predprecWB
Ad-hoc methods for determining the order of variablespreorder
Pretty printing of an fsvsdraws objectprint.fsvdraws
Extract summary statistics for the posterior correlation matrix which have been stored during samplingrunningcormat
Extract summary statistics for the posterior covariance matrix which have been stored during samplingrunningcovmat
A posteriori sign identificationsignident
Plot series-specific volatilities over time.voltimeplot