ci_f_ncp

Based on the inversion principle, parametric CIs for the non-centrality parameter
(NCP) Delta of the F distribution are calculated.
To keep the input interface simple, we do not provide bootstrap CIs here.

Calculates classic and/or bootstrap confidence intervals for
many parameters such as the population mean, variance, interquartile
range (IQR), median absolute deviation (MAD), skewness, kurtosis,
Cramer's V, odds ratio, R-squared, quantiles (incl. median),
proportions, different types of correlation measures, difference in
means, quantiles and medians. Many of the classic confidence intervals
are described in Smithson, M. (2003, ISBN: 978-0761924999). Bootstrap
confidence intervals are calculated with the R package 'boot'. Both
one- and two-sided intervals are supported.

Michael Mayer

confintr

Confidence Intervals

ci_f_ncp function

<dl><dt>x</dt>
<dd>The result of <code><a href="/link/stats%3A%3Alm()?package=confintr&version=1.0.2" data-mini-rdoc="confintr::stats::lm()">stats::lm()</a></code> or the F test statistic.</dd>
<dt>df1</dt>
<dd>The numerator df. Only used if <code>x</code> is a test statistic.</dd>
<dt>df2</dt>
<dd>The denominator df. Only used if <code>x</code> is a test statistic.</dd>
<dt>probs</dt>
<dd>Lower and upper probabilities, by default <code>c(0.025, 0.975)</code>.</dd></dl>

Arguments

CI for the Non-Centrality Parameter of the F Distribution — ci_f_ncp

<dl>

<dt>x</dt>
<dd>The result of <code><a href='https://rdrr.io/r/stats/lm.html'>stats::lm()</a></code> or the F test statistic.</dd>


<dt>df1</dt>
<dd>The numerator df. Only used if <code>x</code> is a test statistic.</dd>


<dt>df2</dt>
<dd>The denominator df. Only used if <code>x</code> is a test statistic.</dd>


<dt>probs</dt>
<dd>Lower and upper probabilities, by default <code>c(0.025, 0.975)</code>.</dd>

</dl>

ci_f_ncp: CI for the Non-Centrality Parameter of the F Distribution

Description

Usage

Value

Arguments

Details

References

See Also

Examples