Usage
runDNAcopy(input, smooth.region=2, outlier.SD.scale = 4, smooth.SD.scale = 2, trim=0.025, alpha = 0.01, p.method = c("hybrid", "perm"), kmax = 25, nmin = 200, undo.splits = c("none", "prune", "sdundo"), undo.prune = 0.05, undo.SD = 3, nperm = 10000, eta = 0.05)
Arguments
smooth.region
number of points to consider on the left and the
right of a point to detect it as an outlier.
outlier.SD.scale
the number of SDs away from the nearest point
in the smoothing region to call a point an outlier.
smooth.SD.scale
the number of SDs from the median in the
smoothing region where a smoothed point is positioned.
trim
proportion of data to be trimmed for variance calculation
for smoothing outliers and undoing splits based on SD.
alpha
significance levels for the test to accept change-points.
p.method
method used for p-value computation. For the "perm"
method the p-value is based on full permutation. For the "hybrid"
method the maximum over the entire region is split into maximum of
max over small segments and max over the rest. Approximation is
used for the larger segment max. Default is hybrid.
kmax
the maximum width of smaller segment for permutation
in the hybrid method.
nmin
the minimum length of data for which the approximation of
maximum statistic is used under the hybrid method.
undo.splits
A character string specifying how change-points are
to be undone, if at all. Default is "none". Other choices are
"prune", which uses a sum of squares criterion, and "sdundo", which
undoes splits that are not at least this many SDs apart.
undo.prune
the proportional increase in sum of squares allowed
when eliminating splits if undo.splits="prune".
undo.SD
the number of SDs between means to keep a split if
undo.splits="sdundo".
nperm
number of permutations used for p-value computation.
eta
the probability to declare a change conditioned on the permuted statistic exceeding the observed statistic exactly j (= 1,...,nperm*alpha) times.