bdpPlotBE

Plot regression posterior pairs with CI Box and MD ellipses

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

bdpPlotBE function

<dl><dt>bdpreg</dt>
<dd>bdpreg object created with bdpreg</dd>
<dt>cov.method</dt>
<dd>rrcov covariance method ("SDe", "MCD", or "Classical"). Default MCD.</dd>
<dt>ci</dt>
<dd>Probability for the HDI credibility interval. Default 0.95.</dd>
<dt>...</dt>
<dd>Arguments passed to <code>plot</code> (e.g. <code>xlim</code>, <code>xlab</code>, <code>main</code>)</dd></dl>

Arguments

Plot regression posterior pairs with CI Box and MD ellipses — bdpPlotBE

<dl>

<dt>bdpreg</dt>
<dd>bdpreg object created with bdpreg</dd>


<dt>cov.method</dt>
<dd>rrcov covariance method ("SDe", "MCD", or "Classical"). Default MCD.</dd>


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


<dt>...</dt>
<dd>Arguments passed to <code>plot</code> (e.g. <code>xlim</code>, <code>xlab</code>, <code>main</code>)</dd>

</dl>

bdpPlotBE: Plot regression posterior pairs with CI Box and MD ellipses

Description

Usage

Value

Arguments