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

In NTS: Nonlinear Time Series Analysis

Sequential Importance Sampling Step for A Target with Passive Sonar

Description

This function implements one step of the sequential importance sampling method for a target with passive sonar.

Usage

Sstep.Sonar(mm, xx, logww, yy, par, xdim = 1, ydim = 1)

Arguments

mm	the Monte Carlo sample size m.
xx	the sample in the last iteration.
logww	the log weight in the last iteration.
yy	the observations with T columns and ydim rows.
par	a list of parameter values. H is the state coefficient matrix, W*t(W) is the state innovation covariance matrix, V*t(V) is the covariance matrix of the observation noise, s2 is the second sonar location.
xdim	the dimension of the state variable x_t.
ydim	the dimension of the observation y_t.

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.