model_eval_fun

Only used internally in <code>{LSTbook}</code>. These were originally arranged as S3
methods, but now the dispatch is done "by hand" in order to eliminate any
exported S3 methods.

"Lessons in Statistical Thinking" D.T. Kaplan (2014)
<https://dtkaplan.github.io/Lessons-in-statistical-thinking/>
is a textbook for a first or second course in statistics that embraces
data wrangling, causal reasoning, modeling, statistical adjustment,
and simulation. 'LSTbook' supports the student-centered, tidy,
pipeline-oriented computing style featured in the book.

Daniel Kaplan

LSTbook

Data and Software for "Lessons in Statistical Thinking"

Randall Pruim

model_eval_fun function

<dl><dt>model</dt>
<dd>A model object of the classes permitted</dd>
<dt>data</dt>
<dd>Usually, a data table specifying the inputs to the model. But if
not specified, the training data will be used.</dd>
<dt>interval</dt>
<dd>One of "none", "confidence", or "prediction". Not all model
types support "prediction" or even "confidence".</dd>
<dt>level</dt>
<dd>(default 0.95) confidence or prediction level. Must be in <code>[0,1]</code></dd>
<dt>...</dt>
<dd>additional arguments</dd></dl>

Arguments

Helper functions to evaluate models — model_eval_fun

<dl>

<dt>model</dt>
<dd>A model object of the classes permitted</dd>


<dt>data</dt>
<dd>Usually, a data table specifying the inputs to the model. But if
not specified, the training data will be used.</dd>


<dt>interval</dt>
<dd>One of "none", "confidence", or "prediction". Not all model
types support "prediction" or even "confidence".</dd>


<dt>level</dt>
<dd>(default 0.95) confidence or prediction level. Must be in <code>[0,1]</code></dd>


<dt>...</dt>
<dd>additional arguments</dd>

</dl>

model_eval_fun: Helper functions to evaluate models

Description

Usage

Value

Arguments