similar to: Unhidden predict methods

Dear All I am a biginner of R. I have difficulty with reading the code of a method. I am using the vars package to estimate a VAR model and I want to view the code of "predict" method for objects with class attribute "varest". I thougt I could just type the name "predict" without anything to display the code of the method as I often do with generic function.

Hello. I just downloaded R onto a new computer, and after entering library(MASS), I still get the message "Error: could not find function "predict.lda"" when I try to use the predict.lda function (even just "predict.lda()") Can anyone help me out? Thank you! Diana Connett

Hi Every Body, I don't know why some regression functions have no related prediction function. For example lowess, loess, lokerns, lpridge, lpepa, and ksmooth. What could help? Is there any global or wrapper function so that can help? Regards, Amir Safari --------------------------------- [[alternative HTML version deleted]]

Oh yes. The "load package" under the "packages menu" in the Windows version does that. To check I typed "library(assist)" after starting R. Same behavior, ssr is found, but others like predict.ssr, and plot.ssr, give a "not found" message. Thanks for the suggestion. Mike

Using > methods("plot") [1] plot.Date* plot.HoltWinters* plot.POSIXct* [4] plot.POSIXlt* plot.TukeyHSD plot.acf* [7] plot.data.frame* plot.decomposed.ts* plot.default [10] plot.dendrogram* plot.density plot.ecdf [13] plot.factor* plot.formula* plot.hclust* [16] plot.histogram* plot.isoreg* plot.lm [19] plot.medpolish*

With the recent changes in R 1.9.x, it is now impossible to properly call plot on a formula() where the formula is provided via a named first argument. On today's R-1.9.1-alpha: > x <- 1:10 > y <- rnorm(x,0.25) > > plot(x~y) > > plot(x=x~y) Error in terms.formula(formula, data = data) : argument is not a valid model > > plot(formula=x~y) Error in

Dear R-Helpers, I suspect I'm about to ask a FAQ, but I haven't been able to find an answer in the FAQ, AItR or an R Site Search. When I look at the methods of summary (below) it says, "Non-visible functions are asterisked". I looked at the help file for summary.princomp, which did not comment on it being non-visible. I ran its help file example, which printed visible output. I

Hi, from the man page ?methods, I expected to be able to build pairs (class,package) for a given S3 method, e.g., print, using attr(methods(print), 'info'). However all the methods, except the ones defined in base or S4 methods, get the 'from' value "registered S3method for print", instead of the actual package name (see below for the first rows). Is this normal

Hi! How to find out which plot function is used when i call plot(hist.default(1:10,plot=F)) and all works fine ? The reason why I would like to know it is that after loading some self written R functions > plot(hist.default(1:10,plot=F)) Error in xy.coords(x, y, xlabel, ylabel, log) : x and y lengths differ > traceback() 5: stop("x and y lengths differ") 4: xy.coords(x, y,

Dear List, This may be related to this email thread initiated by Ben Bolker last month: https://stat.ethz.ch/pipermail/r-devel/2011-July/061630.html In answering this Question on StackOverflow http://stackoverflow.com/q/7195628/429846 I noticed that `methods()` was not listing some S3 methods for `plot()` provided by the mgcv package. At the time I wanted to check the development version of R as

Good Morning! May you help me? I need to understand the function predict. I need to understand the algorithm implemented, the calculations associated. Where can I find this information? Thank You!

Dear list, yet another question on S4 method behaviour or rather its side effects: Consider the following example (see below) where a new S4 method 'predict' is defined which by doing so makes 'predict' a S4 standardGeneric. It works and simple test examples run but I'm cautious whether this is a 'silly' thing to do. Is this a dangerous thing to do, already known to

Dear all, I'm analyzing a binary outcome using glm() with a binomial distribution and a logit link, and have now reached the point where I'd like to do some model checking. Since my data are in binary form I'd like to collapse over the cross-classification of the factors before the model checking. Are there any nice and simple ways doing this? If so, how? If not, I'd be

Hi everyone, I've tried the below on R 1.9.1 and the 2004-08-30 builds of R 1.9.1 Patched and R 2.0.0 on Windows 2000, and the results are consistent. > seq(0.5, 0, by = -0.1) [1] 0.5 0.4 0.3 0.2 0.1 0.0 > seq(0.7, 0, by = -0.1) [1] 7.000000e-01 6.000000e-01 5.000000e-01 4.000000e-01 3.000000e-01 2.000000e-01 1.000000e-01 -1.110223e-16 Is this really the intended behaviour?

>>>>> Henric Winell <nilsson.henric at gmail.com> >>>>> on Tue, 7 Feb 2017 13:37:42 +0100 writes: > Hi, On 2017-02-07 13:12, Benjamin Tyner wrote: >> Hello >> >> When loading a package, I'm wondering if it's frowned >> upon for the package to alter the state of the random >> number

Dear list, I've noticed that influence.measures and cooks.distance gives different results for non-gaussian GLMs. For example, using R-1.9.0 alpha (2003-03-17) under Windows: > ## Dobson (1990) Page 93: Randomized Controlled Trial : > counts <- c(18,17,15,20,10,20,25,13,12) > outcome <- gl(3,1,9) > treatment <- gl(3,3) > glm.D93 <- glm(counts ~ outcome +

Hello, I tried to compile v2.3.1 on Solaris x86 with SUN Pro compilers. I had an error while stats libarary was being compiled and I notice that "-xtarget=generic64" was not passed to f95 while cc used it. Could you tell me how to fix this problem? f95 -PIC -O -I/mounts/devel/SUNWspro/prod/include -c sgram.f -o sgram.o f95 -PIC -O -I/mounts/devel/SUNWspro/prod/include -c

Thank you for your help! I gave you an example, you could run it in R . Maybe you will understand my meaning clearly. x <- data.frame(main.name="AAA", x.name=rep(c("Apply","Watermelon","Lemon","Banana",

Hello, I'm getting the following error message when I try to run 'tsdiag' on what seems to be a valid time series: > tsdiag(small) returns: [Error in tsdiag(small) : no applicable method for "tsdiag"] where small is a little test series where I have isolated this problem (the original has 30-years worth of daily data) When I print it (small), it looks like the

Dear all, I'm a fairly new R user having two questions regarding gam: 1. The prediction example on p. 38 in the mgcv manual. In order to get predictions based on the original data set, by leaving out the 'newdata' argument ("newd" in the example), I get an error message "Warning message: the condition has length > 1 and only the first element will be used in: if