similar to: 3-d point plotting?

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The following commands illustrate a problem with graphing relatively large data sets using the "line" option to plot: temp <- runif(200000) # or whatever other numbers you like; # same thing happens with a sine wave plot(1:200000, temp) # everything fine plot(1:200000, temp, type="l") # data gets cut off The number of points isn't crucial. The cutoff point

Thanks to John Fox, Brian Ripley, and Peter Dalgaard for responding. The short answer (as in Peter Dalgaard's reply, already posted to the list) is that the models I'm concerned with can in fact be compared using ancova. The key fact is that while the parameters may not be nested, the subspaces I'm examining are. An additional note from Prof. Ripley on AIC and BIC (which I quote in

Hello, all. I've got what is probably a simple question about comparison of models using anova, specifically about the situations in which it's valid. I understand, I think, what's going on when the models are strictly nested (as most are in the demo(lm) examples). My question involves what happens when the models aren't strictly nested. In my particular case, I'm doing

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Hi, all. I'm not sure whether this is a problem with ESS or R (or even a feature I don't understand!). Say I've got a function named f.count.these.patterns (as I do -- I'm using actual names in case they're somehow important). I previously had a version called f.count.these.patterns.3, but discarded it because it was worse. So the function is no longer there. If I create a

Hi, all. Does anyone have an equivalent to Splus "peaks", which finds local maxima (with locality defined by a parameter "span")? I thought I'd check whether anyone has done it already before trying to put something together myself. Thanks, Matt Wiener -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I want to run deconvolution of a time series by an impulse or point-spread function through Wiener filter, regularized filter, Lucy-Richardson method, or any other approaches. I searched the CRAN website and the mailing list archive, but could not find any package for such a deconvolution analysis. Does anybody know an existing R function for deconvolution? TIA, Gang

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Hi, all. The following does not behave as I think it should, and as it seems to me it has in the past (although I can't check this easily). I know it happens in both R-0.64.2 and R-0.65.0 on an old Power Computing running Linux-PPC 1999, and in R-0.64.2 on an SGI running Irix 6.5. Try the following: t1 <- data.frame(matrix(rnorm(16), nc=4)) > t1 X1 X2 X3 X4 1 -0.7206945

Matthew Wiener <mcw@ln.nimh.nih.gov> writes: > t1 <- data.frame(matrix(rnorm(16), nc=4)) > t1$X1 <- 1 > t1$X2 <- 2 > print(t1) > Error: dim<- length of dims do not match the length of object Well, it is prototype-compatible. Splus 5.3 does likewise. A way out is t1<-data.frame(unclass(t1)) However, we do seem to have a bug in the area: > t1 <-

Matthew Wiener <mcw@ln.nimh.nih.gov> writes: > t1 <- data.frame(matrix(rnorm(16), nc=4)) > t1$X1 <- 1 > t1$X2 <- 2 > print(t1) > Error: dim<- length of dims do not match the length of object Well, it is prototype-compatible. Splus 5.3 does likewise. A way out is t1<-data.frame(unclass(t1)) However, we do seem to have a bug in the area: > t1 <-

Hi, all. The lower bound in a barplot (or the left bound if you're making a horizontal barplot) is -0.01 no matter what. This causes problems if you're making a barplot of small values (say, < .001), as most of the plot is taken up with blank space beneath the axis, and the bars are squeezed in at the top. The fix seems to be simple: replace lines 41: xlim <- range(-0.01,

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Matthew Wiener <mcw@ln.nimh.nih.gov> writes: > > parameters (xxdefun in gram.y calls lang4). The arg count got changed > > from 0.64.2 to 0.65.0 (from 3 to 4) to accommodate the stored source > > attribute. I suppose that a function stored in a saved workspace might > > cause some kind of mess when restored. > > > > If I understand this correctly, it

Full_Name: Matthew Wiener Version: 1.1.1 OS: linux Submission from: (NULL) (156.40.248.102) I've come across a glitch in hist. I can reproduce it on linux for Intel, linux for PPC, and Irix 6.5. t1 <- c(41, 42, 42, 43, 43, 43, 44, 44, 45, 46) hist(t1, breaks = 10) (OK) hist(t1/50, breaks = 10) Error in hist.defauilt(t1/50, breaks = 10): some 'x' not counted; maybe

Hi, all. The help file for tapply says that if simplify is true, and the result of the calculation is always a scalar, then tapply will return a vector. Nonetheless: > t1 <- tapply(runif(10), rep(1:5, 2), mean) > is.vector(t1) [1] FALSE > is.array(t1) [1] TRUE > I have found this in version 0.65.1 on an SGI running Irix 6.5, and on a Mac running Linux-PPC. I've also

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or