fwdmv.init {Rfwdmv}R Documentation

Multivariate Forward Search for Ungrouped Data

Description

This function computes a multivariate forward search for ungrouped data. Several diagnostic statistics are monitored during the search: see fwdmv.object. Note that this function is called by fwdmv when no tentative groups are specified. It is recommended that fwdmv be used for all multivariate forward searches.

Usage

fwdmv.init(X, bsb = ellipse.subset, n.bsb, scaled = TRUE, monitor = "all")

Arguments

X a matrix or data frame containing the multivariate data set.
bsb a function of two variables: the multivariate data in matrix form X and the number of units in the initial subset size. The default bsb = ellipse.subset computes the initial subset using robustly centered ellipses. Other choices include bsb = bb.subset to compute the initial subset using bivariate boxplots, bsb = mcd.subset to compute the initial subset using mcd distances, and bsb = random.subset for a randomly determined initial subset. Alternatively, the initial subset my be specified directly by providing an integer vector containing the indices of the units to be in the initial subset.
n.bsb a positive integer specifying the size of the initial subset; ignored if bsb is not a function.
scaled a logical value. If TRUE then scaled Mahalanobis distances are used during the forward search.
monitor a character vector specifying which statistics are to be monitored during the forward search. The default value "all" monitors all statistics. Otherwise choose from "distance", "center", "cov", "determinant", "unit", "max", "mth", "min", and "mpo".

Details

This function computes the Forward Search as described in chapter 3 of ARC. The initial subset can be specified directly in the argument bsb or computed from the data. By default bsb is a function for computing the initial subset using robustly centered ellipses. Given a subset of m units the next subset is the m+1 units with smallest Mahalanobis distances calculated using the center and covariance matrix estimates computed from the units currently in the subset. This process is repeated until the subset contains all of the units and diagnostic statistics are monitored for each subset.

Value

an fwdmv object.

Author(s)

Kjell Konis

References

Atkinson, A. C., Riani, M. and Cerioli, A. (2004) Exploring Multivariate Data with the Forward Search. Springer-Verlag New York.

See Also

fwdmv, fwdmv.object

Examples

data(fondi.dat)
fondi.init <- fwdmv.init(fondi.dat)

## find the intial subset using robust bivariate ellipses ##
## start with an initial subset size of 17 units          ##
fondi.init <- fwdmv.init(fondi.dat,bsb=ellipse.subset(fondi.dat,17))

## find the intial subset using bivariate boxplots and ##
## start with an initial subset size of 17 units       ##
fondi.init <- fwdmv.init(fondi.dat,bsb=bb.subset(fondi.dat,17))


[Package Rfwdmv version 0.72-2 Index]