[Robast-commits] r287 - pkg/RobLoxBioC/inst/scripts
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Apr 20 14:58:51 CEST 2009
Author: stamats
Date: 2009-04-20 14:58:51 +0200 (Mon, 20 Apr 2009)
New Revision: 287
Modified:
pkg/RobLoxBioC/inst/scripts/AffySimStudy.R
pkg/RobLoxBioC/inst/scripts/AffySimStudyFunction.R
pkg/RobLoxBioC/inst/scripts/AffymetrixExample.R
Log:
some updates
Modified: pkg/RobLoxBioC/inst/scripts/AffySimStudy.R
===================================================================
--- pkg/RobLoxBioC/inst/scripts/AffySimStudy.R 2009-04-18 15:06:02 UTC (rev 286)
+++ pkg/RobLoxBioC/inst/scripts/AffySimStudy.R 2009-04-20 12:58:51 UTC (rev 287)
@@ -34,28 +34,20 @@
(res4 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(5, 1)
+contD <- Norm(10, 1)
(res5 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(10, 1)
+contD <- Dirac(1.51)
(res6 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(5, 9)
+contD <- Dirac(1000)
(res7 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Dirac(100)
-(res8 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
- eps.lower = eps.lower, eps.upper = eps.upper,
- contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Dirac(1.51)
-(res9 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
- eps.lower = eps.lower, eps.upper = eps.upper,
- contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-eps <- 0.025
+eps <- 0.02
contD <- Norm(0, 9)
(res11 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
@@ -72,28 +64,20 @@
(res14 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(5, 1)
+contD <- Norm(10, 1)
(res15 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(10, 1)
+contD <- Dirac(1.51)
(res16 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(5, 9)
+contD <- Dirac(1000)
(res17 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Dirac(100)
-(res18 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
- eps.lower = eps.lower, eps.upper = eps.upper,
- contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Dirac(1.51)
-(res19 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
- eps.lower = eps.lower, eps.upper = eps.upper,
- contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-eps <- 0.05
+eps <- 0.04
contD <- Norm(0, 9)
(res21 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
@@ -110,23 +94,15 @@
(res24 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(5, 1)
+contD <- Norm(10, 1)
(res25 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(10, 1)
+contD <- Norm(1.51)
(res26 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(5, 9)
+contD <- Dirac(1000)
(res27 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
eps.lower = eps.lower, eps.upper = eps.upper,
contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Dirac(100)
-(res28 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
- eps.lower = eps.lower, eps.upper = eps.upper,
- contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
-contD <- Norm(1.51)
-(res29 <- AffySimStudy(n = n, M = M, eps = eps, seed = seed,
- eps.lower = eps.lower, eps.upper = eps.upper,
- contD = contD, plot1 = FALSE, plot2 = FALSE, plot3 = FALSE))
Modified: pkg/RobLoxBioC/inst/scripts/AffySimStudyFunction.R
===================================================================
--- pkg/RobLoxBioC/inst/scripts/AffySimStudyFunction.R 2009-04-18 15:06:02 UTC (rev 286)
+++ pkg/RobLoxBioC/inst/scripts/AffySimStudyFunction.R 2009-04-20 12:58:51 UTC (rev 287)
@@ -58,17 +58,13 @@
Tukey <- cbind(Tukey, Mad)
## Radius-minimax estimator
- RadMinmax1 <- estimate(rowRoblox(Mre, eps.lower = eps.lower,
+ RadMinmax <- estimate(rowRoblox(Mre, eps.lower = eps.lower,
eps.upper = eps.upper, k = steps,
fsCor = fsCor))
- RadMinmax2 <- estimate(rowRoblox(Mre, sd = Mad, eps.lower = eps.lower,
- eps.upper = eps.upper, k = steps,
- fsCor = fsCor))
- RadMinmax2 <- cbind(RadMinmax2, Mad)
if(plot3){
- Ergebnis1 <- list(Mean, Median, Tukey[,1], RadMinmax1[,1], RadMinmax2[,1])
- Ergebnis2 <- list(Sd, Mad, Tukey[,2], RadMinmax1[,2], RadMinmax2[,2])
+ Ergebnis1 <- list(Mean, Median, Tukey[,1], RadMinmax[,1])
+ Ergebnis2 <- list(Sd, Mad, Tukey[,2], RadMinmax[,2])
myCol <- brewer.pal(4, "Dark2")
if(plot1 || plot2) dev.new()
layout(matrix(c(1, 1, 1, 1, 3, 2, 2, 2, 2, 3), ncol = 2))
@@ -78,7 +74,7 @@
abline(h = 1)
op <- par(mar = rep(2, 4))
plot(c(0,1), c(1, 0), type = "n", axes = FALSE)
- legend("center", c("ML", "Med/MAD", "biweight", "rmx", "rmx/MAD"),
+ legend("center", c("ML", "Med/MAD", "biweight", "rmx"),
fill = myCol, ncol = 5, cex = 1.5)
par(op)
}
@@ -90,11 +86,12 @@
## Tukey
MSE3.1 <- n*mean(Tukey[,1]^2)
## Radius-minimax
- MSE4.1 <- n*mean(RadMinmax1[,1]^2)
- MSE5.1 <- n*mean(RadMinmax2[,1]^2)
- empMSE <- data.frame(ML = MSE1.1, Med = MSE2.1, Tukey = MSE3.1,
- "rmx" = MSE4.1, "rmx1" = MSE5.1)
+ MSE4.1 <- n*mean(RadMinmax[,1]^2)
+ empMSE <- data.frame(ML = MSE1.1, Med = MSE2.1, Tukey = MSE3.1, "rmx" = MSE4.1)
rownames(empMSE) <- "n x empMSE (loc)"
+ relMSE <- empMSE[1,]/empMSE[1,4]
+ empMSE <- rbind(empMSE, relMSE)
+ rownames(empMSE)[2] <- "relMSE (loc)"
## ML-estimator
MSE1.2 <- n*mean((Sd-1)^2)
@@ -103,13 +100,18 @@
## Tukey
MSE3.2 <- MSE2.2
## Radius-minimax
- MSE4.2 <- n*mean((RadMinmax1[,2]-1)^2)
- MSE5.2 <- n*mean((RadMinmax2[,2]-1)^2)
- empMSE <- rbind(empMSE, c(MSE1.2, MSE2.2, MSE3.2, MSE4.2, MSE5.2))
- rownames(empMSE)[2] <- "n x empMSE (scale)"
+ MSE4.2 <- n*mean((RadMinmax[,2]-1)^2)
+ empMSE <- rbind(empMSE, c(MSE1.2, MSE2.2, MSE3.2, MSE4.2))
+ rownames(empMSE)[3] <- "n x empMSE (scale)"
+ relMSE <- empMSE[3,]/empMSE[3,4]
+ empMSE <- rbind(empMSE, relMSE)
+ rownames(empMSE)[4] <- "relMSE (scale)"
empMSE <- rbind(empMSE, c(MSE1.1 + MSE1.2, MSE2.1 + MSE2.2, MSE3.1 + MSE3.2,
- MSE4.1 + MSE4.2, MSE5.1 + MSE5.2))
- rownames(empMSE)[3] <- "n x empMSE (loc + scale)"
+ MSE4.1 + MSE4.2))
+ rownames(empMSE)[5] <- "n x empMSE (loc + scale)"
+ relMSE <- empMSE[5,]/empMSE[5,4]
+ empMSE <- rbind(empMSE, relMSE)
+ rownames(empMSE)[6] <- "relMSE (loc + scale)"
empMSE
}
Modified: pkg/RobLoxBioC/inst/scripts/AffymetrixExample.R
===================================================================
--- pkg/RobLoxBioC/inst/scripts/AffymetrixExample.R 2009-04-18 15:06:02 UTC (rev 286)
+++ pkg/RobLoxBioC/inst/scripts/AffymetrixExample.R 2009-04-20 12:58:51 UTC (rev 287)
@@ -162,8 +162,8 @@
dev.off()
## Comparison of median distances
-abs(sapply(res1, median) - sapply(res3, median))
-abs(sapply(res2, median) - sapply(res3, median)[-c(1,2,4,7)])
+round(sapply(res1, median) - sapply(res3, median), 4)
+round(sapply(res2, median) - sapply(res3, median)[-c(1,2,4,7)], 4)
###########################################################
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