SVfilter: Switching Filter (for Stochastic Volatility Models)

In astsa: Applied Statistical Time Series Analysis

Switching Filter (for Stochastic Volatility Models)

Description

Performs a special case switching filter when the observational noise is a certain mixture of normals. Used to fit a stochastic volatility model.

Usage

SVfilter(num, y, phi0, phi1, sQ, alpha, sR0, mu1, sR1)

Arguments

num	number of observations
y	time series of returns
phi0	state constant
phi1	state transition parameter
sQ	state standard deviation
alpha	observation constant
sR0	observation error standard deviation for mixture component zero
mu1	observation error mean for mixture component one
sR1	observation error standard deviation for mixture component one

Value

xp	one-step-ahead prediction of the volatility
Pp	mean square prediction error of the volatility
like	the negative of the log likelihood at the given parameter values

Note

See Example 6.23 in Chapter 6 of the text.

Author(s)

D.S. Stoffer

References

You can find demonstrations of astsa capabilities at FUN WITH ASTSA.

The most recent version of the package can be found at https://github.com/nickpoison/astsa/.

In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.

The webpages for the texts and some help on using R for time series analysis can be found at https://nickpoison.github.io/.

astsa documentation built on Jan. 10, 2023, 1:11 a.m.