Segmentation using optimal partioning and functional pruning

Description

A wrapper to a C implementation of optimal partioning with functional pruning

Details

Author(s)

Guillem Rigaill

Fpop

Description

Function calling the fpop algorithm, use functional pruning and optimal partioning to recover the best segmentation with respect to the L2 loss with a per change-point penalty of lambda. More precisely, this function computes the solution to argmin_m sum_i=1^n (x_i-m_i)^2 + lambda * sum_i=1^n-1 I(m_i != m_i+1), where the indicator function I counts the number of changes in the mean vector m.

Usage

Fpop(x, lambda, mini = min(x), maxi = max(x))

Arguments

Value

Named list with the following elements: input data (signal, n, lambda, min, max), path (best previous segment end up to each data point), cost (optimal penalized cost up to each data point), t.est (vector of overall optimal segment ends), K (optimal number of segments), J.est (total un-penalized cost of optimal model). To see how cost relates to J.est, see definition of J.est in the R source code for this function.

Author(s)

Guillem Rigaill, Toby Dylan Hocking

Examples

set.seed(1)
N <- 100
data.vec <- c(rnorm(N), rnorm(N, 2), rnorm(N))
fit <- Fpop(data.vec, N)
end.vec <- fit$t.est
change.vec <- end.vec[-length(end.vec)]
start.vec <- c(1, change.vec+1)
segs.list <- list()
for(seg.i in seq_along(start.vec)){
  start <- start.vec[seg.i]
  end <- end.vec[seg.i]
  seg.data <- data.vec[start:end]
  seg.mean <- mean(seg.data)
  segs.list[[seg.i]] <- data.frame(
    start, end,
    mean=seg.mean,
    seg.cost=sum((seg.data-seg.mean)^2))
}
segs <- do.call(rbind, segs.list)
plot(data.vec)
with(segs, segments(start-0.5, mean, end+0.5, mean, col="green"))
with(segs[-1,], abline(v=start-0.5, col="green", lty="dotted"))

fpop analysis

Description

A function to count the number of intervals and or candidate segmentation at each step of fpop (under-developpemment)

Usage

fpop_analysis(x, lambda, mini = min(x), maxi = max(x))

Arguments

Value

return a list with a vector containing the position of the change-points t.est

Author(s)

Guillem Rigaill, Toby Dylan Hocking

multiBinSeg

Description

Binary segmentation of p profiles using the L2 loss

Usage

multiBinSeg(geno, Kmax)

Arguments

Value

return an object with the successive change-points found by binseg t.est and the L2 cost J.est

Author(s)

Guillem Rigaill, Toby Dylan Hocking

retour op

Description

This function is used by the Fpop function to recover the best segment ends from 1:n from the C output.

Usage

retour_op(path)

Arguments

Value

a vector with the best segment ends.

Author(s)

Guillem Rigaill, Toby Dylan Hocking