sim_toad

The simulation function for the toad example.

Bayesian synthetic likelihood (BSL, Price et al. (2018) <doi:10.1080/10618600.2017.1302882>)
is an alternative to standard, non-parametric approximate Bayesian
computation (ABC). BSL assumes a multivariate normal distribution
for the summary statistic likelihood and it is suitable when the
distribution of the model summary statistics is sufficiently regular.
This package provides a Metropolis Hastings Markov chain Monte Carlo
implementation of four methods (BSL, uBSL, semiBSL and BSLmisspec) and two
shrinkage estimators (graphical lasso and Warton's estimator).
uBSL (Price et al. (2018) <doi:10.1080/10618600.2017.1302882>) uses
an unbiased estimator to the normal density. A semi-parametric version
of BSL (semiBSL, An et al. (2018) <arXiv:1809.05800>) is more robust
to non-normal summary statistics. BSLmisspec (Frazier et al. 2019
<arXiv:1904.04551>) estimates the Gaussian synthetic likelihood whilst
acknowledging that there may be incompatibility between the model and the
observed summary statistic. Shrinkage estimation can help to decrease the
number of model simulations when the dimension of the summary statistic is
high (e.g., BSLasso, An et al. (2019) <doi:10.1080/10618600.2018.1537928>).
Extensions to this package are planned. For a journal article describing how
to use this package, see An et al. (2022) <doi:10.18637/jss.v101.i11>.

Leah F. South

Bayesian Synthetic Likelihood

Ziwen An

Christopher C. Drovandi

sim_toad function

<dl><dt>params</dt>
<dd>A vector of proposed model parameters, \(\alpha\),
\(gamma\) and \(p_0\).</dd>
<dt>ntoad</dt>
<dd>The number of toads to simulate in the observation.</dd>
<dt>nday</dt>
<dd>The number of days lasted of the observation.</dd>
<dt>model</dt>
<dd>Which model to be used. 1 for the random return model, 2 for the nearest return model,
and 3 for the distance-based return probability model.</dd>
<dt>d0</dt>
<dd>Characteristic distance for model 3. Only used if model is 3.</dd></dl>

Arguments

The simulation function for the toad example — sim_toad

<dl>

<dt>params</dt>
<dd>A vector of proposed model parameters, \(\alpha\),
\(gamma\) and \(p_0\).</dd>


<dt>ntoad</dt>
<dd>The number of toads to simulate in the observation.</dd>


<dt>nday</dt>
<dd>The number of days lasted of the observation.</dd>


<dt>model</dt>
<dd>Which model to be used. 1 for the random return model, 2 for the nearest return model,
and 3 for the distance-based return probability model.</dd>


<dt>d0</dt>
<dd>Characteristic distance for model 3. Only used if model is 3.</dd>

</dl>

sim_toad: The simulation function for the toad example

Description

Usage

Value

Arguments

Examples