[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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