This function uses the sequential importance sampling method to deal with a target with passive sonar for smoothing.
Sstep.Smooth.Sonar(mm, xxt, xxt1, ww, vv, par)
The function returns a list with the following components:
the new sample.
the log weights.
the Monte Carlo sample size m
.
the sample in the last iteration.
the sample in the next iteration.
the forward filtering weight.
the backward smoothing weight.
a list of parameter values. H
is the state coefficient matrix, and W*t(W)
is the state innovation covariance matrix.
Tsay, R. and Chen, R. (2018). Nonlinear Time Series Analysis. John Wiley & Sons, New Jersey.