bdpCalcResponse

Plot the calculated Y response with CI from the full Bayesian posterior distribution

Regression methods to quantify the relation
between two measurement methods are provided by this package. The
focus is on a Bayesian Deming regressions family. With a Bayesian
method the Deming regression can be run in a traditional fashion or
can be run in a robust way just decreasing the degree of freedom
d.f. of the sampling distribution. With d.f. = 1 an extremely robust
Cauchy distribution can be sampled. Moreover, models for dealing
with heteroscedastic data are also provided. For reference see
G. Pioda (2024) <https://piodag.github.io/bd1/>.

Giorgio Pioda

rstanbdp

Bayesian Deming Regression for Method Comparison

bdpCalcResponse function

<dl><dt>bdpreg</dt>
<dd>bdpreg object</dd>
<dt>Xval</dt>
<dd>Reference method data</dd>
<dt>ci</dt>
<dd>Probability for the HDI credibility interval. Default 0.95.</dd>
<dt>...</dt>
<dd>Arguments passed to <code>hist</code> (e.g. <code>breaks</code>, <code>xlim</code>, ...).</dd></dl>

Arguments

Plot the calculated Y response with CI from the full Bayesian posterior distribution — bdpCalcResponse

<dl>

<dt>bdpreg</dt>
<dd>bdpreg object</dd>


<dt>Xval</dt>
<dd>Reference method data</dd>


<dt>ci</dt>
<dd>Probability for the HDI credibility interval. Default 0.95.</dd>


<dt>...</dt>
<dd>Arguments passed to <code>hist</code> (e.g. <code>breaks</code>, <code>xlim</code>, ...).</dd>

</dl>

bdpCalcResponse: Plot the calculated Y response with CI from the full Bayesian posterior distribution

Description

Usage

Value

Arguments