search for: richard_rauberta

R 1.7.1 on Windows XP The "normal Q-Q plot" produced by plot.lm() mislabels points when the model is fitted using na.action=na.exclude. Example: x <- 1:50 y <- x + rnorm(50) y[c(5,10,15)] <- NA # insert some NA's y[40] <- 50 # add an outlier plot(lm(y ~ x, na.action=na.omit)) # outlier correctly labeled in all # four plots

I am using R 1.7.1 on Windows XP Pro. The 'overwrite=FALSE' argument appears to be ignored in file.copy(): > file.exists(c("file1.txt", "file2.txt")) [1] TRUE TRUE > file.copy(from="file2.txt", to="file1.txt", overwrite=FALSE) [1] TRUE > and sure enough, file1.txt has been overwritten. Rich Raubertas Biometrics Research, RY33-300 Merck

The following command, temp <- read.table("c:/rfr/r/test.txt") reads the text file "test.txt", which contains the following lines: 21437 21438 21419-2 21420-2 21421-2 21422-2 and produces the following result: > temp V1 1 21437+0i 2 21438+0i 3 0+0i 4 0+0i 5 0+0i 6 0+0i > These "numbers" are actually sample ID's, and I

Dear list, Utils::modifyList() drops NULL components in its second argument, instead of adding them to the first argument. Compare: > modifyList(x=list(A=1), val=list(B=2, C=3)) $A [1] 1 $B [1] 2 $C [1] 3 > modifyList(x=list(A=1), val=list(B=NULL, C=3)) $A [1] 1 $C [1] 3 To me this seems inconsistent with the documentation ("Elements in 'val' which are missing from

R 1.8.1 with Windows XP. I have a question about how sd() behaves with NA's: > mean(c(1,2,3,NA)) [1] NA > median(c(1,2,3,NA)) [1] NA > mad(c(1,2,3,NA)) [1] NA > sd(c(1,2,3,NA)) Error in var(x, na.rm = na.rm) : missing observations in cov/cor > What is so special about the standard deviation, relative to other descriptive statistics, that the presence of NA's deserves an

There is a bug in 'anova.gls' in the 'nlme' package (3.1-90). The=20 bug is triggered by calling the function with a single 'gls' object=20 and specifying the 'Terms' argument but not the 'L' argument: > library(nlme) > fm1Orth.gls <- gls(distance ~ Sex * I(age - 11), Orthodont, + correlation =3D corSymm(form =3D ~ 1 |

I am using the dotplot function from the lattice package to display a quantitative variable versus two factors, say 'a' and 'b'. The levels of 'a' are nested within levels of 'b'. The issue is that dotplot includes all the levels of 'a' in each panel (conditioning on 'b'), even though many are empty in any given panel. A toy example is dat

[R 1.7.1 on Windows XP Pro] Since R allows missing values for character variables, why are NA's not propagated by character manipulation functions? For example: > temp <- c("a", NA) > temp [1] "a" NA > is.na(temp) [1] FALSE TRUE > paste(temp[1], temp[2]) [1] "a NA" > substr(temp, 1, 1) [1] "a" "N" >

R 1.6.1 on Windows NT4: The boxplot() function appears to draw its own tick marks and axis values even when called with add=TRUE. As a toy example, try x <- rnorm(100) f <- factor(rep(1:4, each=25)) plot(c(0,4), c(-3,3), type="n", xaxt="n", yaxt="n") boxplot(x ~ f, add=TRUE) My expectation is that a high-level plotting function will not mess with the axes

For nested function calls it appears that a combination of environment() and '<<-' will also work: f1 <- function() { x <- rep(NA,4) # Object to be modified by function f2 environment(f2) <- sys.frame(1) # Make f1's environment available to f2 f2(2) # Changes 2nd element of x print(x) } f2 <- function(i) { #