similar to: Problem with % in an example when running R CMD check

Dear R help, I'm having some trouble with model formulas for the ols function in the rms package. I want to have two variables represented as restricted cubic splines, and also include an interaction as a product of linear terms, but I get an error message. library(rms) d <- data.frame(x1 = rnorm(50), x2 = rnorm(50), y = rnorm(50)) ols(y ~ rcs(x1,3) + rcs(x2,3) + x1*x2, data=d) Error in

Hi, Running the following example from ?Predict() throws an error I have never seen before: set.seed(1) x1 <- runif(300) x2 <- runif(300) ddist <- datadist(x1,x2); options(datadist='ddist') y <- exp(x1+ x2 - 1 + rnorm(300)) f <- ols(log(y) ~ pol(x1,2) + x2) p1 <- Predict(f, x1=., conf.type='mean') Error in paste(nmc[i], "=", if (is.numeric(x))

Robin, the initial output from apply() is always in the form you have below, but if it can be 'simplified' into a structure like the matrix, it does so. The same thing happens with sapply(). If you want to produce a nice matrix as the out put you have to ensure that the simplification is possible. Here is one way. > apply(x2, 2, function(x, v) table(factor(x, levels=v)),

Consider the code: x <- seq(0,1,0.2) y <- seq(0,1,0.01) cbind(match(y,x),y) which, surprisingly, doesn't show a match at 0.6! (It gives correct matches at 0, 0.2, 0.4, 0.8 and 1, though) In addition, x[4]==y[61] yields FALSE. (but x[5]==y[81], the one for 0.8, yields TRUE) Is this a consequence of machine error or something else? Could this be overcome? (It works correctly when

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Hello all, I want to assign relative score to the predictor variables on the basis of its influence on the dependent variable. But I could not find any standard statistical approach appropriate for this purpose. Please suggest the possible approaches. Thanks in advance, Rupendra Chulyadyo Institute of Engineering, Tribhuvan University, Nepal [[alternative HTML version deleted]]

Dear R Users! I&#39;m new in R! I&#39;ve got a data.frame. For example:a<-data.frame(cbind( 0:1, 1:10)) X1 X2 1 0 1 2 1 2 3 0 3 4 1 4 5 0 5 6 1 6 7 0 7 8 1 8 9 0 9 10 1 10 Firstly i want to create combinations from X2, for example:combn(a$X2,2) It&#39;s ok, butsecondly I would like to get combinations from those X2 numbers only , where X1= 0. Could

Hi dear all, suppose that s is a statistic code; i have a matrix (x) which has 7 columns (1=x1,2=x23=x3,4=x4,5=x5,6=x6 and7=y) and has 20 rows. i want to do linear reggression like reg<-lm(x[,7]~1+x[,1]+x[,2]+.......+x[,6]) but i want to do delete i th row for nrows times and create regression model like above and compute each models' "s" statistics and list them. but i could

Greetings. I've written a convenience function for multicollinearity diagnosis. I'd like to report to the user the formula that is used in a regression. I get output like this: > mcDiagnose(m1) [1] "The following auxiliary models are being estimated and returned in a list:" [1] "`x1` ~ ." formula(fmla)() [1] "`x2` ~ ." I'd like to fill in the period

I have no direct experience with such horrific models, but your formula is a mess and Google suggests the biglm package with ffdf. Specifically, you should convert your discrete variables to factors before you build the model, particularly since you want to use predict after the fact, for which you will need a new data set with the exact same levels in the factors. Also, your use of I() is

Hello, I think I am beginning to understand what is involved in the so-called "Type-I, II, ..." ANOVAS (thanks to all the replies I got for yesterday's post). I have a question that will help me (and others?) understand it better (or remove a misunderstanding): I know that ANOVA is really a special case of regression where the predictor variable is categorical. I know that there

Dear all, I am running a panel regression with time and location fixed effects: ### reg1 <- lm(lny ~ factor(id) + factor(year) + x1+ I(x1)^2 + x2+ I(x2)^2 , data=mydata, na.action="na.omit") ### My goal is to use the estimation for prediction. However, I have 8,500 IDs, which is resulting in very slow computation. Ideally, I would like to do the following: ### reg2 <-

Dear list: I encountered some problems using the function point.in.polygon() of the sp package, when trying to determine whether some points lye inside, outside, on the border or on a vertice of a polygon. I have a list of point I know should lye right on the border of a polygon, but some of them are not classified as such by point.in.polygon() (see the example code below). To make a long story

Hello, I just realized that my second DC does not recognize the users from the AD. wbinfo -u/-g are working just fine. [root at dc1 ~]# id bruno.castro uid=10004(POL\bruno.castro) gid=100(users) grupos=100(users),10001(POL\ti),3000009(BUILTIN\users) [root at dc2 ~]# id bruno.castro id: bruno.castro: no such user [root at dc1 ~]# wbinfo -i bruno.castro POL\bruno.castro:*:10004:100:Bruno de

Could someone tell me how to access the log likelihood of a poisson model? I've done the following.... <BEGIN R STUFF> freq.mod <- glm(formula = nfix ~ gls.gls + pol.gls + pol.rel + rac.gls + rac.pol + rac.rac + rac.rel + white + gls.gls.w + pol.gls.w + pol.rel.w + rac.gls.w + rac.pol.w + rac.rac.w + rac.rac.w + rac.rel.w, family = poisson, data = Complex2.freq, offset = lnoffset)

hello, I am using following command classify_polarity(documents,algorithm="bayes",verbose=TRUE) output is: [1] "DOCUMENT 1" [1] "WORD: excited CAT: positive POL: strongsubj SCORE: 8.44419229853175" [1] "WORD: happy CAT: positive POL: strongsubj SCORE: 8.44419229853175" [1] "WORD: optimistic CAT: positive POL: weaksubj SCORE: 7.7510451179718" [1]

I've been trying to get some code to run on a 64-bit FreeBSD machine running R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.0 (2006-04-24) ISBN 3-900051-07-0 and keep getting a core dump with the following results: *** caught segfault *** address 0x0, cause 'unknown' Traceback: 1: .Call("R_point_in_polygon_sp", as.numeric(point.x),

Dear Jan, Thank you very much for your excellent description of the problem and the self-contained test code. This is a problem that I've been meaning to either document better or solve for some time. The root of the problem is with the builtin S-Plus terms.inner function: > attr(terms.inner(asthma ~ pol(age,kx) + smok),'variables') expression(age, kx, smok) You can see that

I have recently set up an small SAMBA network(just my server and a W2K SP4 Workstation). My Server is acting as a PDC. Everything seems to work flawlessly, users, roaming profiles, netlogon script, etc... But I cannot make this machine to read my NTConfig.pol file. I have it at my NETLOGON share [/srv/netlogon] with rwxr-xr-x permissions. I have tried with different filenames (NTConfig.POL,

I am running Samba 2.2.7a on SuSE 8.0 and all Windows/XP clients in a PDC configuration. All runs great except for one problem. I cannot get NTconfig.pol to be used. I have placed it in the netlogon share and read/execute permissions are wide open. I turn on samba loglevel=3 and I never see samba even try to look for NTconfig.pol, or any *.pol file. This occurs for all of my clients. Any