mewma

Generates a Hotelling's T2 Graph for <code>mewma</code> objects.

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

mewma function

<dl><dt>X</dt>
<dd>a dataframe.</dd><dt>phase</dt>
<dd>designates whether the confidence limits should reflect the current data frame, <code>phase = 1</code> or future observations, <code>phase = 2</code>.</dd><dt>lambda</dt>
<dd>EWMA smoothing parameter</dd><dt>conf</dt>
<dd>the confidence level(s) to use for upper control limit.</dd><dt>asymptotic.form</dt>
<dd>use asymptotic convergence parameter for scaling the covariance matrix.</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

Generates a Hotelling's T2 Graph of the Multivariate Exponentially Weighted Average — mewma

<dl>

<dt>X</dt>
<dd>a dataframe.</dd>

<dt>phase</dt>
<dd>designates whether the confidence limits should reflect the current data frame, <code>phase = 1</code> or future observations, <code>phase = 2</code>.</dd>

<dt>lambda</dt>
<dd>EWMA smoothing parameter</dd>

<dt>conf</dt>
<dd>the confidence level(s) to use for upper control limit.</dd>

<dt>asymptotic.form</dt>
<dd>use asymptotic convergence parameter for scaling the covariance matrix.</dd>

</dl>

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

mewma: Generates a Hotelling's T2 Graph of the Multivariate Exponentially Weighted Average

Description

Usage

Value

Arguments

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Examples