wrap.SMC {NTS}

Sequential Monte Carlo Using Sequential Importance Sampling for Stochastic Volatility Models

Description

The function implements the sequential Monte Carlo method using sequential importance sampling for stochastic volatility models.

Usage

wrap.SMC(par.natural, yy, mm, setseed = T, resample = T)

Arguments

par.natural

contains three parameters in AR(1) model. The first one is the stationary mean, the second is the AR coefficient, and the third is stationary variance.

yy

the data.

mm

the Monte Carlo sample size.

setseed

the seed number.

resample

the logical value indicating for resampling.

Value

The function returns the log-likelihood of the data.

References

Tsay, R. and Chen, R. (2018). Nonlinear Time Series Analysis. John Wiley & Sons, New Jersey.