[Robast-commits] r897 - branches/robast-1.1/pkg/ROptEst/R
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sun Sep 4 16:39:37 CEST 2016
Author: ruckdeschel
Date: 2016-09-04 16:39:37 +0200 (Sun, 04 Sep 2016)
New Revision: 897
Removed:
branches/robast-1.1/pkg/ROptEst/R/getFiRisk.R
Log:
deleted getFiRisk from pkg ROptEst in branch 1.1
Deleted: branches/robast-1.1/pkg/ROptEst/R/getFiRisk.R
===================================================================
--- branches/robast-1.1/pkg/ROptEst/R/getFiRisk.R 2016-09-04 14:37:46 UTC (rev 896)
+++ branches/robast-1.1/pkg/ROptEst/R/getFiRisk.R 2016-09-04 14:39:37 UTC (rev 897)
@@ -1,198 +0,0 @@
-###############################################################################
-## finite-sample under-/overshoot risk
-###############################################################################
-
-# cdf of truncated normal distribution
-ptnorm <- function(x, mu, A, B){
- ((A <= x)*(x <= B)*(pnorm(x-mu)-pnorm(A-mu))/(pnorm(B-mu)-pnorm(A-mu))
- + (x > B))
-}
-
-# n-fold convolution for truncated normal distributions
-conv.tnorm <- function(z, A, B, mu, n, m){
- if(n == 1) return(ptnorm(z, mu = mu, A = A, B = B))
- if(z <= n*A) return(0)
- if(z >= n*B) return(1)
-
- M <- 2^m
- h <- (B-A)/M
- x <- seq(from = A, to = B, by = h)
- p1 <- ptnorm(x, mu = mu, A = A, B = B)
- p1 <- p1[2:(M + 1)] - p1[1:M]
-
- ## FFT
- pn <- c(p1, numeric((n-1)*M))
-
- ## convolution theorem for DFTs
- pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
- pn <- (abs(pn) >= .Machine$double.eps)*pn
- i.max <- n*M-(n-2)
- pn <- c(0,pn[1:i.max])
- pn <- cumsum(pn)
-
- ## cdf with continuity correction h/2
- x <- c(n*A,seq(from = n*A+n/2*h, to = n*B-n/2*h, by=h),n*B)
- pnfun1 <- approxfun(x = x+0.5*h, y = pn, yleft = 0, yright = pn[i.max+1])
- pnfun2 <- function(x) pnfun1(x) / pn[i.max+1]
-
- return(pnfun2(z))
-}
-
-
-setMethod("getFiRisk", signature(risk = "fiUnOvShoot",
- Distr = "Norm",
- neighbor = "ContNeighborhood"
- ),
- function(risk, Distr, neighbor, clip, stand,
- sampleSize, Algo, cont){
- eps <- neighbor at radius
- tau <- risk at width
- n <- sampleSize
- m <- getdistrOption("DefaultNrFFTGridPointsExponent")
-
- if(Algo == "B"){
- if(cont == "left"){
- delta1 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
- K1 <- dbinom(0:n, size = n, prob = delta1)
- P1 <- (1-eps)*pnorm(-clip-tau) + eps
- p1 <- P1/delta1
-
- summe1 <- numeric(n+1)
- summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
- summe1[n+1] <- (1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
- + pbinom(q = n/2-0.1, size = n, prob = p1)))
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
- summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
- }
- erg <- sum(summe1*K1)
- }else{
- delta2 <- (1-eps)*(pnorm(-clip+tau) + pnorm(-clip-tau)) + eps
- K2 <- dbinom(0:n, size = n, prob = delta2)
- P2 <- (1-eps)*pnorm(-clip+tau)
- p2 <- P2/delta2
-
- summe2 <- numeric(n+1)
- summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
- summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
- + pbinom(q = n/2-0.1, size = n, prob = p2))
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
- summe2[k+1] <- sum(P2.ste*dbinom(j, size=k, prob=p2))
- }
- erg <- sum(summe2*K2)
- }
- }else{
- M <- 2^m
- h <- 2*clip/M
- x <- seq(from = -clip, to = clip, by = h)
-
- if(cont == "right"){
- p1 <- pnorm(x+tau)
- p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
- p1[1] <- p1[1] + (1-eps)*pnorm(-clip+tau)
- p1[M] <- p1[M] + (1-eps)*pnorm(-clip-tau) + eps
- }else{
- p1 <- pnorm(x-tau)
- p1 <- (1-eps)*(p1[2:(M + 1)] - p1[1:M])
- p1[1] <- p1[1] + (1-eps)*pnorm(-clip-tau) + eps
- p1[M] <- p1[M] + (1-eps)*pnorm(-clip+tau)
- }
-
- ## FFT
- pn <- c(p1, numeric((n-1)*M))
-
- ## convolution theorem for DFTs
- pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
- pn <- (abs(pn) >= .Machine$double.eps)*pn
- pn <- cumsum(pn)
-
- k <- n*(M-1)/2
- erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
- if(cont == "right") erg <- 1 - erg
- }
-
- return(list(fiUnOvShoot = erg))
- })
-
-setMethod("getFiRisk", signature(risk = "fiUnOvShoot",
- Distr = "Norm",
- neighbor = "TotalVarNeighborhood"),
- function(risk, Distr, neighbor, clip, stand, sampleSize, Algo, cont){
- delta <- neighbor at radius
- tau <- risk at width
- n <- sampleSize
- m <- getdistrOption("DefaultNrFFTGridPointsExponent")
-
- if(Algo == "B"){
- if(cont == "left"){
- delta1 <- min(pnorm(-clip-tau)+delta, 1) + 1 - min(pnorm(clip-tau)+delta, 1)
- K1 <- dbinom(0:n, size = n, prob = delta1)
- P1 <- min(pnorm(-clip-tau) + delta, 1)
- p1 <- min(P1/delta1, 1)
-
- summe1 <- numeric(n+1)
- summe1[1] <- 1 - conv.tnorm(z = 0, A = -clip, B = clip, mu = -tau, n = n, m = m)
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P1.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = -tau, n = n-k, m = m)
- summe1[k+1] <- sum((1-P1.ste)*dbinom(j, size = k, prob = p1))
- }
- summe1[n+1] <- 1 - 0.5*(pbinom(q = n/2, size = n, prob = p1)
- + pbinom(q = n/2-0.1, size = n, prob = p1))
- erg <- sum(summe1*K1)
- }else{
- delta2 <- max(0, pnorm(-clip+tau)-delta) + 1 - max(0, pnorm(clip+tau)-delta)
- K2 <- dbinom(0:n, size = n, prob = delta2)
- P2 <- max(0, pnorm(-clip+tau) - delta)
- p2 <- P2/delta2
-
- summe2 <- numeric(n+1)
- summe2[1] <- conv.tnorm(z = 0, A = -clip, B = clip, mu = tau, n = n, m = m)
- for(k in 1:(n-1)){
- j <- 0:k
- z <- clip*(k-2*j)
- P2.ste <- sapply(z, conv.tnorm, A = -clip, B = clip, mu = tau, n = n-k, m = m)
- summe2[k+1] <- sum(P2.ste*dbinom(j, size = k, prob = p2))
- }
- summe2[n+1] <- 0.5*(pbinom(q = n/2, size = n, prob = p2)
- + pbinom(q = n/2-0.1, size = n, prob = p2))
- erg <- sum(summe2*K2)
- }
- }else{
- M <- 2^m
- h <- 2*clip/M
- x <- seq(from = -clip, to = clip, by = h)
-
- if(cont == "right"){
- p1 <- pnorm(x+tau)
- p1 <- p1[2:(M + 1)] - p1[1:M]
- p1[1] <- p1[1] + pnorm(-clip+tau) - delta
- p1[M] <- p1[M] + pnorm(-clip-tau) + delta
- }else{
- p1 <- pnorm(x-tau)
- p1 <- p1[2:(M + 1)] - p1[1:M]
- p1[1] <- p1[1] + pnorm(-clip-tau) + delta
- p1[M] <- p1[M] + pnorm(-clip+tau) - delta
- }
-
- ## FFT
- pn <- c(p1, numeric((n-1)*M))
-
- ## convolution theorem for DFTs
- pn <- Re(fft(fft(pn)^n, inverse = TRUE)) / (n*M)
- pn <- (abs(pn) >= .Machine$double.eps)*pn
- pn <- cumsum(pn)
-
- k <- n*(M-1)/2
- erg <- ifelse(n%%2 == 0, (pn[k]+pn[k+1])/2, pn[k+1])
- if(cont == "right") erg <- 1-erg
- }
-
- return(list(fiUnOvShoot = erg))
- })
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