SVM: Constructor of an Stochastic volatility model object

In bayesforecast: Bayesian Time Series Modeling with Stan

Description

Constructor of the Stochastic Volatility model (SVM) for Bayesian estimation in Stan.

Usage

SVM(ts,arma = c(0,0),xreg = NULL,series.name = NULL)

Arguments

ts	a numeric or ts object with the univariate time series.
arma	Optionally, a specification of the ARMA model,same as order parameter: the two components (p, q) are the AR order,and the MA order.
xreg	Optionally, a numerical matrix of external regressors, which must have the same number of rows as ts. It should not be a data frame.
series.name	an optional string vector with the time series names.

Details

The function returns a list with the data for running stan() function of rstan package.

Value

The function returns a list with the data for running stan() function of rstan package.

Author(s)

Asael Alonzo Matamoros

References

Sangjoon,K. and Shephard, N. and Chib.S (1998). Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models. Review of Economic Studies. 65(1), 361-93. url: https://www.jstor.org/stable/2566931.

Tsay, R (2010). Analysis of Financial Time Series. Wiley-Interscience. 978-0470414354, second edition.

Shumway, R.H. and Stoffer, D.S. (2010).Time Series Analysis and Its Applications: With R Examples. Springer Texts in Statistics. isbn: 9781441978646. First edition.

See Also

garch set_prior

Examples

# Declares a SVM model for the IPC data

model = SVM(ipc,arma = c(1,1))
model

bayesforecast documentation built on June 17, 2021, 5:14 p.m.