ekf_smoother

object

<p>If <code>iekf_iter &gt; 0</code>, iterated extended Kalman filter is 
used with <code>iekf_iter</code> iterations.</p>

iekf_iter

<p>Function <code>ekf_smoother</code> runs the (iterated) extended Kalman smoother for 
the given non-linear Gaussian model of class <code>nlg_ssm</code>, 
and returns the filtered estimates and one-step-ahead predictions of the 
states \(\alpha_t\) given the data up to time \(t\).</p>

Efficient methods for Bayesian inference of state space models
via particle Markov chain Monte Carlo and parallel importance sampling type weighted
Markov chain Monte Carlo (Vihola, Helske, and Franks, 2017, <arXiv:1609.02541>).
Gaussian, Poisson, binomial, or negative binomial
observation densities and basic stochastic volatility models with Gaussian state
dynamics, as well as general non-linear Gaussian models and discretised diffusion models
are supported.

Jouni Helske

ekf_smoother: Extended Kalman Smoothing

Description

Usage

Arguments

Value