CONS (version 0.1.0)

CONS: Consonance Analysis Module

Description

Consonance Analysis is a useful numerical and graphical approach for evaluating the consistency of the measurements and the panel of people involved in sensory evaluation. It makes use of several uni and multivariate techniques either graphical or analytical.

You can learn more about this package at: http://www.uv.mx/personal/nehuerta/cons/

Usage

CONS()

Value

CONS is a graphic interface

Details

CONS is a package with a graphical interface that performs Consonance Analysis. This procedure is an approach useful for evaluating the consistency of the measurements performed by a panel of people involved in sensory evaluation. It makes use of several uni and multivariate techniques either graphical or analytical. The procedure helps evaluate the linearirty of an attribute with respect to the panel performance. If there is evidence that an attribute is not linear then this information could be used to improve the evaluation of such characteristic. The method also helps detect whether some members of the panel deviate from the rest. A critical tool for this procedure is Principal Components Analysis.

References

Arnold GM, Williams AA (1985). "The Use of Generalised Procrusters Analysis in Sensory Analysis". In JR Piggot (ed.) Statistical Procedures in Food Research. North Holland, Amsterdam.

Banfield CF, Harries JM (1975). " A Techniques for Comparing Judges' Performance in Sensory Tests". Journal of Food Technology, 10, 1-10.

Dijksterhuis GB, Gower JC (1991/92). "The Interpretation of Generalised Procrusters Analysis and Allied Methods". Food Quality and Preference, 3, 67-87.

Dijksterhuis GB (1995). "Assessing Panel Consonance". Food Quality and Preference, 6(1):714. http://dx.doi.org/10.1016/0950-3293(94)P4207-M

Dijksterhuis GB (2004). "Assessing Panel Consonance". Multivariate Data Analysis in Sensory and Consumer Science. ISBN: 978-0-917678-41-7. DOI: 10.1002/9780470385050.ch2

Gower JC (1975). "Generalised Procrusters Analysis." Psychometrika, 40, 33-51.

Sebastien Le, Julie Josse, Francois Husson (2008). FactoMineR: An R Package for Multivariate Analysis. Journal of Statistical Software, 25(1), 1-18. 10.18637/jss.v025.i01

van der Burg E (1988). "Nonlinear Canonical Correlation and Some Related Techniques." DSWO press, Leiden.

van der Burg E, Dijksterhuis GB (1989). "Nonlinear Canonical Correlation Analysis of Multiway Data". In R Coppi, S Bolasco (eds.) Multiway Data Analysis, 245-255. North-Holland, Elsevier Science Publishers B.V.

Examples

## Not run: 
# ##Install package
# library(CONS)
# ##Call the package
# CONS()
# ## End(Not run)