MVcis

Calculate joint confidence intervals (Hotelling's T2 Intervals).

An open-source implementation of latent variable methods and multivariate modeling tools. The focus is on exploratory analyses using dimensionality reduction methods including low dimensional embedding, classical multivariate statistical tools, and tools for enhanced interpretation of machine learning methods (i.e. intelligible models to provide important information for end-users).   Target domains include extension to dedicated applications e.g. for manufacturing process modeling, spectroscopic analyses, and data mining.

Nelson Afanador

mvdalab

Multivariate Data Analysis Laboratory

MVcis function

<dl><dt>data</dt>
<dd>a multivariable dataset to compare to means</dd><dt>segments</dt>
<dd>number of line-segments used to draw ellipse.</dd><dt>level</dt>
<dd>draw elliptical contours at these (normal) probability or confidence levels.</dd><dt>Vars2Plot</dt>
<dd>variables to plot</dd><dt>include.zero</dt>
<dd>add the zero axis to the graph output</dd></dl>

Arguments

Nelson Lee Afanador (<a href="/link/nelson.afanador%40mvdalab.com?package=mvdalab&version=1.7" data-mini-rdoc="mvdalab::nelson.afanador@mvdalab.com">nelson.afanador@mvdalab.com</a>)

Author

Calculate Hotelling's T2 Confidence Intervals — MVcis

<dl>

<dt>data</dt>
<dd>a multivariable dataset to compare to means</dd>

<dt>segments</dt>
<dd>number of line-segments used to draw ellipse.</dd>

<dt>level</dt>
<dd>draw elliptical contours at these (normal) probability or confidence levels.</dd>

<dt>Vars2Plot</dt>
<dd>variables to plot</dd>

<dt>include.zero</dt>
<dd>add the zero axis to the graph output</dd>

</dl>

Nelson Lee Afanador (<a href='mailto:nelson.afanador@mvdalab.com'>nelson.afanador@mvdalab.com</a>)

MVcis: Calculate Hotelling's T2 Confidence Intervals

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples