preprocess_JAR

For JAR data, this preprocessing is needed.

Hierarchical and partitioning algorithms to cluster blocks of variables. The partitioning algorithm includes an option called noise cluster to set aside atypical blocks of variables. The CLUSTATIS method (for quantitative blocks) (Llobell, Cariou, Vigneau, Labenne & Qannari (2020) <doi:10.1016/j.foodqual.2018.05.013>, Llobell, Vigneau & Qannari (2019) <doi:10.1016/j.foodqual.2019.02.017>) and the CLUSCATA method (for Check-All-That-Apply data) (Llobell, Cariou, Vigneau, Labenne & Qannari (2019) <doi:10.1016/j.foodqual.2018.09.006>, Llobell, Giacalone, Labenne & Qannari (2019) <doi:10.1016/j.foodqual.2019.05.017>) are the core of this package. The CATATIS methods allows to compute some indices and tests to control the quality of CATA data. Multivariate analysis and clustering of subjects for quantitative multiblock data, CATA, RATA, Free Sorting and JAR experiments are available. Clustering of rows in multi-block context (notably with ClusMB strategy) is also included.

Fabien Llobell

ClustBlock

Clustering of Datasets

Evelyne Vigneau

Veronique Cariou

El Mostafa Qannari

preprocess_JAR function

<dl><dt>Data</dt>
<dd>data frame where the first column is the Assessors, the second is the products and all other columns the JAR attributes with numbers (1 to 3 or 1 to 5, see levelsJAR)</dd>
<dt>nprod</dt>
<dd>integer. Number of products.</dd>
<dt>nsub</dt>
<dd>integer. Number of subjects.</dd>
<dt>levelsJAR</dt>
<dd>integer. 3 or 5 levels. If 5, the data will be transformed in 3 levels.</dd>
<dt>beta</dt>
<dd>numerical. Parameter for agreement between JAR and other answers. Between 0 and 0.5.</dd></dl>

Arguments

Preprocessing for Just About Right Data — preprocess_JAR

<dl>

<dt>Data</dt>
<dd>data frame where the first column is the Assessors, the second is the products and all other columns the JAR attributes with numbers (1 to 3 or 1 to 5, see levelsJAR)</dd>


<dt>nprod</dt>
<dd>integer. Number of products.</dd>


<dt>nsub</dt>
<dd>integer. Number of subjects.</dd>


<dt>levelsJAR</dt>
<dd>integer. 3 or 5 levels. If 5, the data will be transformed in 3 levels.</dd>


<dt>beta</dt>
<dd>numerical. Parameter for agreement between JAR and other answers. Between 0 and 0.5.</dd>

</dl>

preprocess_JAR: Preprocessing for Just About Right Data

Description

Usage

Value

Arguments

References

See Also

Examples