\name{discontSmooth} \alias{discontSmooth} \title{ A discontinuous smoother } \description{ Calculates discontinuous smoother } \usage{ discontSmooth(y,gamma) } \arguments{ \item{y}{ input vector } \item{gamma}{ The \code{gamma} level can be roughly compared to the sliding window size in a normal continuous smoother. The \code{gamma} level determines how strict the algorithm functions; a higher level will correspond to fewer jumps. This cannot be larger than \code{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 \code{y} } \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 } \author{ Sander Bollen } \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) } \keyword{smooth}