discontSmooth: A discontinuous smoother

Description Usage Arguments Details Value Author(s) References Examples

View source: R/discontPlot.R

Description

Calculates discontinuous smoother

Usage

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Arguments

y

input vector

gamma

The gamma level can be roughly compared to the sliding window size in a normal continuous smoother. The gamma level determines how strict the algorithm functions; a higher level will correspond to fewer jumps. This cannot be larger than length(y). Must be a positive integer.

Details

Uses the potts filter algorithm described by Friedrich et al.

Value

Vector with same length as input y

Author(s)

Sander Bollen

References

Friedrich, F., Kempe, a, Liebscher, V., & Winkler, G. (2008). Complexity Penalized M-Estimation. Journal of Computational and Graphical Statistics, 17(1), 201-224. doi:10.1198/106186008X285591

Examples

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#generate piecewise vector with gaussian noise
y <- 1:450
y[1:150] <- 2
y[151:300] <- 3
y[301:450] <- 1
y <- y + rnorm(450)

#calculate smoother
y_smooth <- discontSmooth(y,20)

CAFE documentation built on Nov. 8, 2020, 7:44 p.m.