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

Description Usage Arguments Value References

View source: R/SMC.r

Description

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

Usage

1
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 Aug. 6, 2020, 5:08 p.m.

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