brittleness

A plastic product is produced in three parallel reactors (TK104, TK105, or TK107).
For each row in the dataset, we have the same batch of raw material that was split, and fed to the 3 reactors.
These values are the brittleness index for the product produced in the reactor. A simulated data set.

datasets

New tools for the visualization of missing and/or imputed values
are introduced, which can be used for exploring the data and the structure of
the missing and/or imputed values. Depending on this structure of the missing
values, the corresponding methods may help to identify the mechanism generating
the missing values and allows to explore the data including missing values.
In addition, the quality of imputation can be visually explored using various
univariate, bivariate, multiple and multivariate plot methods. A graphical user
interface available in the separate package VIMGUI allows an easy handling of
the implemented plot methods.

Matthias Templ

Visualization and Imputation of Missing Values

Alexander Kowarik

Andreas Alfons

Gregor de Cillia

Bernd Prantner

Wolfgang Rannetbauer

brittleness function

A data frame with 23 observations on the following 3 variables.<dl>
<dt>TK104</dt>
<dd>Brittleness for batches of raw material in reactor 104</dd><dt>TK105</dt>
<dd>Brittleness for batches of raw material in reactor 105</dd><dt>TK107</dt>
<dd>Brittleness for batches of raw material in reactor 107</dd>
</dl>

Format

Brittleness index data set — brittleness

A data frame with 23 observations on the following 3 variables.<dl>
<dt>TK104</dt>
<dd>Brittleness for batches of raw material in reactor 104</dd>

<dt>TK105</dt>
<dd>Brittleness for batches of raw material in reactor 105</dd>

<dt>TK107</dt>
<dd>Brittleness for batches of raw material in reactor 107</dd>


</dl>

brittleness: Brittleness index data set

Description

Arguments

Format

Examples