LLAsimobj {LLAhclust}R Documentation

Computes similarities among objects

Description

Computes similarities among objects using the likelihood linkage analysis approach proposed by Lerman. The likelihood linkage analysis method mainly consists in replacing the value of the similarity coefficient between two objects by the probability of finding a lower value under the hypothesis of absence of link. See the references below for more details.

Usage

LLAsimobj(x, method = "LLAeuclidean", upper = FALSE)

Arguments

x a numeric matrix or data frame.
method Can be one of LLAeuclidean, LLAcosinus, LLAcategorical, LLAordinal, or LLAboolean. The two first methods can be used to compute similiarty coefficients between objects described by numerical variables.
upper logical value indicating whether the upper triangle of the similarity matrix should be printed by print.LLAsim.

Details

The following functions are also defined for objects of class LLAsim: names.LLAsim, format.LLAsim, as.matrix.LLAsim and print.LLAsim.

Value

Returns an object of class LLAsim whose attributes are very similar to those of objects of class dist. See dist for more details.

References

I.C. Lerman (1981), Classification et analyse ordinale de donnés, Dunod, Paris.

I.C. Lerman (1991), Foundations of the likelihood linkage analysis classification method, Applied Stochastic Models and Data Analysis, 7, pages 63–76.

I.C. Lerman (1993), Likelihood linkage analysis classification method: An example treated by hand, Biochimie, 75, pages 379–397.

I.C. Lerman, Ph. Peter and H. Leredde (1993), Principes et calculs de la méthode implantée dans le programme CHAVL (Classification Hiérarchique par Analyse de la Vraisemblance des Liens), Modulad, 12, pages 33-101.

See Also

LLAsimvar,
as.LLAsim,
LLAhclust,
LLAparteval,
dist.

Examples

data(USArrests)

## Compute similarities between objects based on
## a local Euclidean distance (see references above):
s <- LLAsimobj(USArrests)
s

[Package LLAhclust version 0.2-2 Index]