sis: Sequential Importance Sampling with Prior kernel for 1-D NLSS

In nickpoison/nltsa: Nonlinear Time Series Analysis

Description

Runs sequential importance sampling without resamplingon a given Non-Linear State Space models with prior kernel as proposal.

Usage

  sis(nlss, y, N)

Arguments

nlss	Non-linear state space model
y	Sequence of observations. Its length T is the number of timesteps.
N	Number of particles
resampling	Resampling scheme to use

Details

This algorithm is not recommended and included for illustrative purposes only. This version is therefore a minimalistic and only supports NLLS with univariate states. Use sisr instead.

The variant siskernel allows for arbitrary proposal kernel.

Value

A list with the following components:

particles	Array (T, N) of the sampled particles
logweights	Array (T, N) of the logarithm of the non-normalized importance weights of the particles
weights	Array (T, N) of the normalized importance weights of the particles
t	Indices 1 to T, included for ease of plotting

See Also

siskernel sisr

nickpoison/nltsa documentation built on May 23, 2019, 4:48 p.m.