Sstep.Smooth.Sonar: Sequential Importance Sampling for A Target with Passive...

In NTS: Nonlinear Time Series Analysis

Sequential Importance Sampling for A Target with Passive Sonar

Description

This function uses the sequential importance sampling method to deal with a target with passive sonar for smoothing.

Usage

Sstep.Smooth.Sonar(mm, xxt, xxt1, ww, vv, par)

Arguments

mm	the Monte Carlo sample size m.
xxt	the sample in the last iteration.
xxt1	the sample in the next iteration.
ww	the forward filtering weight.
vv	the backward smoothing weight.
par	a list of parameter values. H is the state coefficient matrix, and W*t(W) is the state innovation covariance matrix.

Value

The function returns a list with the following components:

xx	the new sample.
logww	the log weights.

References

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

NTS documentation built on Sept. 25, 2023, 1:08 a.m.