discontSmooth {CAFE} | R Documentation

## A discontinuous smoother

### Description

Calculates discontinuous smoother

### Usage

    discontSmooth(y,gamma)

### 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

    #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)

[Package CAFE version 1.26.0 Index]