.check_params_match

Helper function to validate input of user-defined functions and priors

internal

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

bayesSSM

Bayesian Methods for State Space Models

.check_params_match function

<dl><dt>init_fn</dt>
<dd>A function to initialize the state-space model.</dd>
<dt>transition_fn</dt>
<dd>A function that defines the state transition of the
state-space model.</dd>
<dt>log_likelihood_fn</dt>
<dd>A function that calculates the log-likelihood
for the state-space model given latent states.</dd>
<dt>pilot_init_params</dt>
<dd>A vector of initial parameter values.</dd>
<dt>log_priors</dt>
<dd>A list of functions for computing the log-prior of each
parameter.</dd></dl>

Arguments

Helper function to validate input of user-defined functions and priors — .check_params_match

<dl>

<dt>init_fn</dt>
<dd>A function to initialize the state-space model.</dd>


<dt>transition_fn</dt>
<dd>A function that defines the state transition of the
state-space model.</dd>


<dt>log_likelihood_fn</dt>
<dd>A function that calculates the log-likelihood
for the state-space model given latent states.</dd>


<dt>pilot_init_params</dt>
<dd>A vector of initial parameter values.</dd>


<dt>log_priors</dt>
<dd>A list of functions for computing the log-prior of each
parameter.</dd>

</dl>

.check_params_match: Helper function to validate input of user-defined functions and priors

Description

Usage

Arguments