partuniq: Classifies Data According to Unique Observations
In mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
partuniq R Documentation
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 May 29, 2024, 8:06 a.m.
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| partuniq | R Documentation |
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)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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