add.gams {UCS} | R Documentation |
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
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 <- ds.find.am(ds) 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)