fitted.bcp: Extract model fitted values

Description

fitted method for class ``bcp''.

Usage

fitted.bcp(object, ...)

Arguments

object

the result of a call to `bcp'.

...

additional arguments.

Value

Fitted values extracted from the `bcp' object.

References

Bai J., Perron P. (2003), Computation and Analysis of Multiple Structural Change Models, Journal of Applied Econometrics, 18, 1-22. url: http: //qed.econ.queensu.ca/jae/2003-v18.1/bai-perron/. Daniel Barry and J. A. Hartigan (1993), A Bayesian Analysis for Change Point Problems, Journal of The American Statistical Association, 88, 309-19. Olshen, A. B., Venkatraman, E. S., Lucito, R., Wigler, M. (2004), Circular binary segmentation for the analysis of array-based DNA copy number data, Biostatistics, 5, 557-572. url: http://www.bioconductor.org/repository/release1.5/package/html/DNAcopy.html. Martyn Plummer, Nicky Best, Kate Cowles, and Karen Vines (2006), The coda Package, version 0.10-7, CRAN: The Comprehensive R Network. Snijders et al. (2001), Assembly of microarrays for genome-wide measurement of DNA copy number, Nature Genetics, 29, 263-264. Achim Zeileis, Friedrich Leisch, Bruce Hansen, Kurt Hornik, Christian Kleiber (2006), The strucchange Package, version 1.3-1, CRAN: The Comprehensive R Network.

Examples

Run this code

##### A random sample from a few normal distributions #####
  testdata <- c(rnorm(20), rnorm(10, 5, 1), rnorm(20))
  bcp.0 <- bcp(testdata)
  summary.bcp(bcp.0)
  plot.bcp(bcp.0)
  fitted.bcp(bcp.0)
  
  ##### Coriell chromosome 11 #####
  data(coriell)
  chrom11 <- as.vector(na.omit(coriell$Coriell.05296[coriell$Chromosome==11]))
  bcp.11 <- bcp(chrom11)
  summary.bcp(bcp.11)
  plot.bcp(bcp.11)
  fitted.bcp(bcp.11)
  
  # to see bcp and Circular Binary Segmentation results run:
  if(require("DNAcopy")) {
  bcp.11$posterior.prob[length(bcp.11$posterior.brob)] <- 0
  n <- length(chrom11)
  cbs <- segment(CNA(chrom11, rep(1, n), 1:n), verbose = 0)
  cbs.ests <- rep(unlist(cbs$output[6]), unlist(cbs$output[5]))
  op <- par(mfrow=c(2,1),col.lab="black",col.main="black")
  plot(1:n, bcp.11$posterior.mean, type="l", xlab="Location", ylab="Posterior Mean", main="Posterior Means")
  lines(cbs.ests, col="red")
  points(chrom11)
  plot(1:n, bcp.11$posterior.prob, type="l", ylim=c(0,1), xlab="Location", ylab="Posterior Probability of a Change", main="Change Point Locations")
  for(i in 1:(dim(cbs$output)[1]-1)) abline(v=cbs$output$loc.end[i], col="red")
  par(op)
  } else {
	cat("DNAcopy is not loaded")
  }
  
  ##### RealInt #####
  data("RealInt")
  bcp.ri <- bcp(as.vector(RealInt))
  summary.bcp(bcp.ri)
  plot.bcp(bcp.ri)
  fitted.bcp(bcp.ri)
  
  # to see bcp and Bai and Perron results run:
  if(require("strucchange")) {
  bcp.ri$posterior.prob[length(bcp.ri$posterior.brob)] <- 0
  bp <- breakpoints(RealInt ~ 1, h = 2)$breakpoints
  rho <- rep(0, length(RealInt))
  rho[bp] <- 1
  b.num<-1 + c(0,cumsum(rho[1:(length(rho)-1)]))
  bp.mean <- unlist(lapply(split(RealInt,b.num),mean))
  bp.ri <- rep(0,length(RealInt))
  for(i in 1:length(bp.ri)) bp.ri[i] <- bp.mean[b.num[i]]
  op <- par(mfrow=c(2,1),col.lab="black",col.main="black")
  xax <- seq(1961, 1987, length=103)
  plot(xax, bcp.ri$posterior.mean, type="l", xlab="Time", ylab="Mean", main="Posterior Means")
  lines(xax, bp.ri, col="blue")
  points(RealInt)
  plot(xax, bcp.ri$posterior.prob, type="l", ylim=c(0,1), xlab="Time", ylab="Posterior Probability", main="Posterior Probability of a Change")
  for(i in 1:length(bp.ri)) abline(v=xax[bp[i]], col="blue")
  par(op)
  } else {
  cat("strucchange is not loaded")
  }