Complete disjoined coded data (binary coding)
Transform a factor in separate variables (one per level) with a binary code (0 for absent, 1 for present) in each variable
disjoin(x)
x |
a vector containing a factor data |
Use cut() to transform a numerical variable into a factor variable
a matrix containing the data with binary coding
Frédéric Ibanez (ibanez@obs-vlfr.fr), Philippe Grosjean (phgrosjean@sciviews.org)
Fromentin J.-M., F. Ibanez & P. Legendre, 1993. A phytosociological method for interpreting plankton data. Mar. Ecol. Prog. Ser., 93:285-306.
Gebski, V.J., 1985. Some properties of splicing when applied to non-linear smoothers. Comput. Stat. Data Anal., 3:151-157.
Grandjouan, G., 1982. Une méthode de comparaison statistique entre les répartitions des plantes et des climats. Thèse d'Etat, Université Louis Pasteur, Strasbourg.
Ibanez, F., 1976. Contribution à l'analyse mathématique des événements en Ecologie planctonique. Optimisations méthodologiques. Bull. Inst. Océanogr. Monaco, 72:1-96.
# Artificial data with 1/5 of zeros Z <- c(abs(rnorm(8000)), rep(0, 2000)) # Let the program chose cuts table(cut(Z, breaks=5)) # Create one class for zeros, and 4 classes for the other observations Z2 <- Z[Z != 0] cuts <- c(-1e-10, 1e-10, quantile(Z2, 1:5/5, na.rm=TRUE)) cuts table(cut(Z, breaks=cuts)) # Binary coding of these data disjoin(cut(Z, breaks=cuts))[1:10, ]
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