PeakSegDP (version 2017.08.15)

cDPA: cDPA

Description

A constrained dynamic programming algorithm (cDPA) can be used to compute the best segmentation with respect to the Poisson likelihood, subject to a constraint on the number of segments, and the changes which must alternate: up, down, up, down, ...

Usage

cDPA(count, weight = rep(1, length(count)), maxSegments)

Arguments

count

Integer vector of count data to segment.

weight

Data weights (normally this is the number of base pairs).

maxSegments

Maximum number of segments to consider.

Examples

# NOT RUN {
fit <- cDPA(c(0, 10, 11, 1), maxSegments=3)
stopifnot(fit$ends[3,4] == 3)
stopifnot(fit$ends[2,3] == 1)
# }