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factorstochvol (version 0.8.1)

Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models

Description

Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility models. Sparsity can be achieved through the usage of Normal-Gamma priors on the factor loading matrix.

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Install

install.packages('factorstochvol')

Monthly Downloads

534

Version

0.8.1

License

GPL (>= 2)

Maintainer

Gregor Kastner

Last Published

August 31st, 2016

Functions in factorstochvol (0.8.1)

corelement

Extract "true" model-implied correlations of two series only
corimageplot

Plot correlation matrices for certain points in time
covmat

Generic extraction of covariance matrix
covmat.fsvsim

Extract "true" model-implied covariance matrix for several points in time
comtimeplot

Plot comunalities over time.
covmat.fsvdraws

Extract posterior draws of the model-implied covariance matrix
covelement

Extract "true" model-implied covariances of two series only
facloadcredplot

Displays bivariate marginal posterior distribution of factor loadings.
corplot

Plots pairwise correlations over time
cortimeplot

Plot correlations over time.
logret

Computes the log returns of a vector-valued time series
facloadpairplot

Displays bivariate marginal posterior distributions of factor loadings.
logvartimeplot

Plot log-variances over time.
facloaddensplot

Density plots of factor loadings draws
ledermann

Ledermann bound for the number of factors
fsvsim

Simulate data from a factor SV model
facloadpointplot

Displays point estimates of the factor loadings posterior.
factorstochvol-package

Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models through MCMC
facloadtraceplot

Trace plots of factor loadings draws
fsvsample

Markov Chain Monte Carlo (MCMC) Sampling for the Factor Stochastic Volatility Model.
paratraceplot

Trace plots of parameter draws
predprecision

Predicts precision matrix and its determinant (Woodbury variant)
predloglikWB

Evaluates the predictive log likelihood using the Woodbury identity
predcor

Predicts correlation matrix
orderident

A posteriori factor order identification
predloglik

Evaluates the predictive log likelihood using the predicted covariance matrix
predcov

Predicts covariance matrix
predcond

Predicts means and variances conditionally on the factors
predh

Predicts factor and idiosyncratic log-volatilities h
plot.fsvdraws

Several factor SV plots
preorder

Ad-hoc methods for determining the order of variables
signident

A posteriori sign identification
print.fsvdraws

Pretty printing of an fsvsdraws object
runningcormat

Extract summary statistics for the posterior correlation matrix which have been stored during sampling
voltimeplot

Plot series-specific volatilities over time.
runningcovmat

Extract summary statistics for the posterior covariance matrix which have been stored during sampling