Decomposition of inertia (i.e. contributions) in multivariate methods
Computes the decomposition of inertia to measure the contributions of row and/or columns in multivariate methods
## S3 method for class 'dudi' inertia(x, row.inertia = FALSE, col.inertia = FALSE, ...) ## S3 method for class 'inertia' print(x, ...) ## S3 method for class 'inertia' summary(object, sort.axis = 1, subset = 5, ...)
x, object |
a duality diagram, object of class |
row.inertia |
if TRUE, returns the decomposition of inertia for the rows |
col.inertia |
if TRUE, returns the decomposition of inertia for the columns |
sort.axis |
the kept axis used to sort the contributions in decreasing order |
subset |
the number of rows and/or columns to display in the summary |
... |
further arguments passed to or from other methods |
Contributions are printed in percentage and the sign is the sign of the coordinates
An object of class inertia, i.e. a list containing :
tot.inertia |
repartition of the total inertia between axes |
row.contrib |
contributions of the rows to the total inertia |
row.abs |
absolute contributions of the rows (i.e. decomposition per axis) |
row.rel |
relative contributions of the rows |
row.cum |
cumulative relative contributions of the rows (i.e. decomposition per row) |
col.contrib |
contributions of the columns to the total inertia |
col.abs |
absolute contributions of the columns (i.e. decomposition per axis) |
col.rel |
relative contributions of the columns |
col.cum |
cumulative relative contributions of the columns (i.e. decomposition per column) |
nf |
the number of kept axes |
Daniel Chessel
Stéphane Dray stephane.dray@univ-lyon1.fr
Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr
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Lebart, L., Morineau, L. and Warwick, K.M. (1984) Multivariate descriptive analysis: correspondence and related techniques for large matrices, John Wiley and Sons, New York.
Greenacre, M. (1984) Theory and applications of correspondence analysis, Academic Press, London, 66.
Rouanet, H. and Le Roux, B. (1993) Analyse des données multidimensionnelles, Dunod, Paris, 143–144.
Tenenhaus, M. (1994) Méthodes statistiques en gestion, Dunod, Paris, p. 160, 161, 166, 204.
Lebart, L., Morineau, A. and Piron, M. (1995) Statistique exploratoire multidimensionnelle, Dunod, Paris, p. 56,95-96.
data(housetasks) coa1 <- dudi.coa(housetasks, scann = FALSE) res <- inertia(coa1, col = TRUE, row = FALSE) res summary(res)
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