sisr: Particle filter via Sequential Importance Sampling with...

In nickpoison/nltsa: Nonlinear Time Series Analysis

Description

Runs a particle filter on a given Non-Linear State Space models

Usage

  sisr(nlss, y, N, proposal.rnd = prior.rnd,
    proposal.logpdf = prior.logpdf,
    resampling = ResidualMultinomialR,
    initial.proposal.rnd = initial.rnd,
    initial.proposal.logpdf = initial.logpdf)

Arguments

nlss	Non-linear state space model
y	Sequence of observations. Its length T is the number of timesteps.
N	Number of particles
proposal.rnd	Function sampling from the proposal kernel to use
proposal.logpdf	Function computing the log-pdf of the proposal kernel
initial.proposal.rnd	Function sampling from the proposal kernel to use at initial timestep
initial.proposal.logpdf	Function computing the log-pdf of the proposal kernel at initial timestep
resampling	Resampling scheme to use

Value

A list with the following components:

particles	Array (T, N, D) 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
ancestors	Array (T, N) of the index of the ancestor of each particle in the previous generation
t	Indices 1 to T, included for ease of plotting
success	TRUE if the filtering succeeded

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