add.gams {UCS}R Documentation

Annotate Data Set with GAM Scores (gam)


Annotates data set with GAM scores, possibly overwriting existing scores of a standard AM. Optionally, jitter annotated in the data set can be taken into account when computing the scores.


  add.gams(ds, names, jitter=FALSE)


ds a UCS data set object
name a character vector specifying the names of generalised association measures to be annotated in the data set
add.jitter if TRUE, random jitter (which must be annotated in the data set) is added to the frequency signatures before computing GAM scores (see details below)


The add.gams function uses the standard variable names for AM scores (e.g. am.t.score for the t.score measure), so that existing scores for the respective standard AMs in the data set will be overwritten. Rankings for the GAM scores can then be computed in the normal way using the add.ranks function.

With jitter=TRUE, a small amount of random jitter is added to the frequency signatures in order to avoid ties in the rankings and facilitate visualisation of the data set. The necessary jitter vectors have to be stored in special variables in the data set first, which is most easily achieved with the add.jitter function.


a copy of the data set ds annotated with GAM scores for the specified measures

See Also

gam.score, gam.iso, builtin.gams, add.ranks, add.jitter


ds <- add.ranks(add.gams(ds, c("t.score", "chi.squared.corr")))

ds <- add.jitter(ds)		
gam.names <-
gam.names <- gam.names[ is.builtin.gam(gam.names) ]
ds <- add.gams(ds, gam.names, jitter=TRUE)
ds <- add.ranks(ds, gam.names, randomise=FALSE, overwrite=TRUE)

[Package UCS version 0.5 Index]