Fpsn: Fpsn

In fpopw: Weighted Segmentation using Functional Pruning and Optimal Partioning

Fpsn

Description

Function to run the pDPA algorithm (Rigaill 2010 and 2015). It uses functional pruning and segment neighborhood. It optimizes the L2-loss for 1 to Kmax changes.

Usage

Fpsn(x, Kmax, mini = min(x), maxi = max(x))

Arguments

x	a numerical vector to segment
Kmax	max number of segments (segmentations in 1 to Kmax segments are recovered).
mini	minimum mean segment value to consider in the optimisation
maxi	maximum mean segment value to consider in the optimisation

Value

return a list with a matrix t.est containing the change-points of the segmentations in 1 to Kmax changes and, the cost J.est in 1 to Kmax changes.

Examples

x <- c(rnorm(100), rnorm(10^3)+2, rnorm(1000)+1)
res <- Fpsn(x=x, K=100)
select.res <- select_Fpsn(res, method="givenVariance")
smt <- getSMT(res, select.res)

fpopw documentation built on June 7, 2022, 1:09 a.m.