partuniq: Classifies Data According to Unique Observations

In mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Classifies Data According to Unique Observations

Description

Gives a one-to-one mapping from unique observations to rows of a data matrix.

Usage

partuniq(x)

Arguments

x	Matrix of observations.

Value

A vector of length nrow(x) with integer entries. An observation k is assigned an integer i whenever observation i is the first row of x that is identical to observation k (note that i <= k).

See Also

partconv

Examples

set.seed(0)

mat <- data.frame(lets = sample(LETTERS[1:2],9,TRUE), nums = sample(1:2,9,TRUE))
mat

ans <- partuniq(mat)
ans

partconv(ans,consec=TRUE)

mclust documentation built on Nov. 16, 2023, 5:10 p.m.