particle_filter

The package provides several particle filter implementations for state-space
models for estimating the intractable marginal likelihood
\(p(y_{1:T}\mid \theta)\):<ul>
<li><code>auxiliary_filter</code></li>
<li><code>bootstrap_filter</code></li>
<li><code>resample_move_filter</code></li>
</ul>The simplest one is the <code>bootstrap_filter</code>, and is thus
recommended as a starting point.

Implements methods for Bayesian analysis of State Space Models.
Includes implementations of the Particle Marginal Metropolis-Hastings
algorithm described in Andrieu et al. (2010)
<doi:10.1111/j.1467-9868.2009.00736.x> and automatic tuning inspired by
Pitt et al. (2012) <doi:10.1016/j.jeconom.2012.06.004> and J. Dahlin and
T. B. Schön (2019) <doi:10.18637/jss.v088.c02>.

Bjarke Hautop

particle_filter: Particle filter functions

Description

Arguments