similar to: matching of arguments in ...?

Hi, I am trying to write a function to compute many cross-tabulations with the -svytable- command. Here is a simplified example of the structure of my code (adapted from the -svytable- help file): data(api) func.example<-function(variable){ dclus1<-svydesign(id=~1, weights=~pw,data=apiclus1, fpc=~fpc) svytable(~ variable, dclus1) } When I call this function with:

Hi there I'm trying to fit a logistic regression model to data that looks very similar to the data in the sample below. I don't understand why I'm getting this error; none of the data are proportional and the weights are numeric values. Should I be concerned about the warning about non-integer successes in my binomial glm? If I should be, how do I go about addressing it? I'm

Howdy, Referencing the below exchange: https://stat.ethz.ch/pipermail/r-help/2006-April/103862.html I am still getting the same warning ("non-integer #successes in a binomial glm!") when using svyglm:::survey. Using the API data: library(survey) data(api) #stratified sample dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)

Hi dears, I expect that Mr Thomas Lumley will read this message. I have data from a complexe stratified survey. The population is divide in 12 regions and a region consist to and urban area and rural one. there to region just with urbain area. stratification variable is a combinaison of region and area type (urban/rural) In rural area, subdivision are sample with probabilties proporionnal to

-------------------------------------------------- From: "Ahoussou Sylvie" <sylvie.ahoussou at antilles.inra.fr> Sent: Friday, September 12, 2008 9:48 AM To: "Thomas Lumley" <tlumley at u.washington.edu> Subject: Re: [R] Complex sampling survey _ Use of survey package > Thanks for your answer > > I think I made a mistake when I recopied the 5 first rows of

The survexp function can fail when called from another function. The "why" of this has me baffled, however. Here is a simple test case, using a very stripped down version of survexp: survexp.test <- function(formula, data, weights, subset, na.action, rmap, times, cohort=TRUE, conditional=FALSE, ratetable=survexp.us, scale=1, npoints, se.fit,

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

Hi all, I'm having some difficulty passing arguments into lm() from within a function, and I was hoping someone wiser in the ways of R could tell me what I'm doing wrong. I have the following: lmwrap <- function(...) { wts <- somefunction() print(wts) # This works, wts has the values I expect fit <- lm(weights=wts,...) return(fit) } If I call my function lmwrap, I get

Wanting a commandline solution (for a problem detailed @ http://mailman.unidata.ucar.edu/mailing_lists/archives/netcdfgroup/2012/msg00279.html ) I turned to Rscript, and whacked out the q'n'd https://github.com/TomRoche/GEIA_to_netCDF/blob/master/netCDF.stats.to.stdout.r However it wasn't as quick as hoped, because I spent quite a bit of time figuring out how to pass the arguments.

In a previous message I was not clear enough in my querry. I have the following program: tst<- function() { x <- c(32.7,32.3,31.5,32.1,29.7,29.1,35.7,35.9,33.1, 36.0,34.2,31.2,31.8,28.0,29.2,38.2,37.8,31.9, 32.5,31.1,29.7) g <- rep(1:7,rep(3,7)) s <- rep(1:3,7) cat(" Only x and g \n") aov1(x,g) cat("\n\n Now x, g and s \n") aov1(x,g,s=s) }

Hi R users, could someone help me to find out which formulas, for standard error calculation, are used in following example: a=data.frame(weights=rep(c(10,1),c(4,1)),fpc=rep(41,5),uk=rep(1,5)) srs<-svydesign(id=~1, weights=~weights, data=a) srs1<-svydesign(id=~1, weights=~weights,fpc=~fpc, data=a) svytotal(~uk,srs) total SE uk 41 9 svytotal(~uk,srs1) total SE uk 41

Hi, is there a way to retrieve the line number of where en error occurred when sourcing a file in a tryCatch statement? Is it stored somewhere accessible? It is not found in the error object. Consider the following code/output and note the difference in the traceback between source (has line number) and sys.source (has no line number). Thank you, Renaud ######## # code ######## codefile <-

Dear R Users, I have searched through the archives but I am still struggling to find a way to process the below dataset. I have a dataset that has stratum and plot identifier. Within each plot there is variable (Top) stating the number of measurments that should be used to to calculate the mean to the largest "top" elements within one of the vectors (X). I would like to process

After using options(error=recover), it takes a long time (too long) to get back to the prompt. Look at: Browse[1]> recover() Enter a frame number, or 0 to exit 1: window(test, start = c(15, 1), end = c(17, 1), extend = TRUE) 2: window.ts(test, start = c(15, 1), end = c(17, 1), extend = TRUE) 3: as.ts(window.default(x, ...)) 4: window.default(x, ...) 5: function () 6: eval(quote(browser()),

Hi, I am getting an error message when I am trying to run the debugger() on the last.dump. The debugger() stops after I make a selection. Could someone please suggest what it might mean? The R log is included below. This is R-1.8.1 on RH 7.3. Thanks, Vadim > load("last.dump.rda") > debugger(last.dump) Message: Error in split(x, f) : Group length is 0 but data length > 0

Hi It seems that names of the form "..#" and "..." are not fixed by make.names(), even though they are reserved words. The documentation reads: > [...] Names such as ".2way" are not valid, and neither are the reserved words. > Reserved words in R: [...] ... and ..1, ..2 etc, which are used to refer to arguments passed down from a calling function, see

Shouldn't the following 4 ways to alter an object in a locked environment either all work or all fail? (All working would be nice, I think.) E <- new.env() assign("var", c(1,2,3,4), envir=E) lockEnvironment(E, bindings=FALSE) E$var[1] <- 101 ; E$var #[1] 101 2 3 local(var[2] <- 102, envir=E) #Error in eval(expr, envir, enclos) : # cannot add

Hi, I'm confused about the use of ellipsis in function arguments. I'm trying to write a wrapper for plot to automate the combination of plot() and points() calls for a data.frame. Some arguments seem to get passed through to the inner plot, while others cause an error: Error in eval(expr, envir, enclos) : ..1 used in an incorrect context, no ... to look in As a minimal example: tmp

I am absolutely new to R and I am aware of only a few basic command lines. I was running a robust regression in R, using the following command line library (MASS) rfdmodel1 <- rlm (TotalEmployment_2004 ~ MISSISSIPPI + LOUISIANA + TotalEmployment_2000 + PCWhitePop_2004 + UnemploymentRate_2004 + PCUrbanPop2000 + PCPeopleWithACollegeDegree_2000 + PCPopulation.of.or.over.65.years.of.age_2004)