map_from_density

Find maximum a posteriori estimate using posterior samples

Implements the Agnostic Fay-Herriot model, an extension of
the traditional small area model. In place of normal sampling errors, the
sampling error distribution is estimated with a Gaussian process to
accommodate a broader class of distributions. This flexibility is most
useful in the presence of bounded, multi-modal, or heavily skewed sampling
errors.

Marten Thompson

agfh

Agnostic Fay-Herriot Model for Small Area Statistics

Snigdhansu Chatterjee

map_from_density function

<dl> <dt>param.ts</dt>
<dd>vector of scalar samples</dd> <dt>plot</dt>
<dd>boolean, plot or not</dd> </dl>

Arguments

Calculate the MAP Estimate from Posterior Samples — map_from_density

<dl>

 <dt>param.ts</dt>
<dd>vector of scalar samples</dd>

 <dt>plot</dt>
<dd>boolean, plot or not</dd>

 </dl>

map_from_density: Calculate the MAP Estimate from Posterior Samples

Description

Usage

Value

Arguments

Details

Examples