segout {segclust} | R Documentation |
Extraction of parameters for segmentation model
out <- segclustout(x,K,th,draw,vh=TRUE)
x |
data vector (without missing values) |
K |
number of segments |
th |
estimated positions for breakpoints for segmentation models up to Kmax segments (t.est from segmean) |
draw |
TRUE for plotting |
vh |
Variance homogeneity, default = TRUE |
output |
dataframe containing results of the estimation procedure |
output$signal |
input signal x |
output$mean |
estimated mean according to the model, for each position |
output$sd |
estimated standard deviation according to the model, for each position |
output$bp |
breakpoint coordinates, equals 1 for a breakpoint (corresponding to the end of the segments) |
F. Picard, M. Hoebecke
Picard, F., Robin, S., Lebarbier, E., & Daudin, J. -J. (2007). A segmentation/clustering model for the analysis of array CGH data. Biometrics, 63(3) 758-766
x1 <- rnorm(20,0,1) x2 <- rnorm(30,2,1) x3 <- rnorm(10,0,1) x4 <- rnorm(40,2,1) x <- c(x1,x2,x3,x4) Kmax <- 20 out <- segmean(x,Kmax) Kselect <- segselect(out$J.est,Kmax) output <- segout(x,K=Kselect,th = out$t.est,draw=TRUE)