Wang_Chen_Sim

Fifty observations where 'D' represents depth, 'L' represents length, and 'W' represents width.

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

Wang_Chen_Sim function

A simulated data frame with 50 observations and the following 3 variables.<dl>
 <dt><code>D</code></dt>
<dd>depth</dd> <dt><code>L</code></dt>
<dd>length</dd> <dt><code>W</code></dt>
<dd>width</dd> 
</dl>

Format

Simulated process data from a plastics manufacturer. — Wang_Chen_Sim

A simulated data frame with 50 observations and the following 3 variables.<dl>
 <dt><code>D</code></dt>
<dd>depth</dd>

 <dt><code>L</code></dt>
<dd>length</dd>

 <dt><code>W</code></dt>
<dd>width</dd>

 
</dl>

Wang_Chen_Sim: Simulated process data from a plastics manufacturer.

Description

Usage

Arguments

Format