similar to: How to get warning about implicit factor to integer coercion?

Hi I noticed a small inconsistency when using sum() vs cumsum() I have a char-based series > tryjpy$long [1] "0.0022" "-0.0002" "-0.0149" "-0.0023" "-0.0342" "-0.0245" "-0.0022" [8] "0.0003" "-0.0001" "-0.0004" "-0.0036" "-0.001" "-0.0011"

I tried to reproduce a result from a former colleague which he got with S-plus bootstrap method. I don't have S-plus at hand. In R, there are 2 packages related to bootstrap method, bootstrap and boot. The former has a function called 'bootstrap' but this does not seem to conform either to the function used in S-plus nor to that described in MASS, 3d ed., p.144. The latter seems to be

>>>>> Tomas Kalibera >>>>> on Tue, 25 Aug 2020 09:29:05 +0200 writes: > On 8/23/20 5:02 PM, Rory Winston wrote: >> Hi >> >> I noticed a small inconsistency when using sum() vs cumsum() >> >> I have a char-based series >> >> > tryjpy$long >> >> [1]

We get caught occasionally, and we all receive spam; sorry for the last one (on R-help). Of course, there will never be a 100% sure prevention... Question is what should happen when mail from R-help to an adressee is refused with the following message : At least I won't be able to easily send e-mail to them {and am not willing to use a non-easy way}.... ----- Transcript of session

Hi, there was a memory improvement done in R going from R 3.3.3 to R 3.4.0 when it comes to comparing an integer 'x' an double 'y' (either may be scalar or vector). For example, in R 3.3.3, I get: > getRversion() [1] '3.3.3' > x <- integer(1000) > y <- double(1000) > profmem::profmem(z <- (x < y)) Rprofmem memory profiling of: z <- (x < y)

I am seeking for a method to calculate, given a fitted lme model and some data for a subject, the random effects predictors for this subject. I can only find predictors for the subjects used in creating the fit. Of course I could just add the subject and redo the fit. But I want to avoid just this refitting. Thanks for help wbk

On May 16, 2009, at 7:47 PM, Luke Dalessandro wrote: > Owen Anderson wrote: >> Some of you may have noticed that I addedd include/llvm/System/ >> Atomics.h >> to the repository briefly, which will be used for adding support for >> threading in LLVM. > > Just out of curiosity, is there a design document somewhere for the > plan > for threading? Not as

Hi, I have a dataframe that I imported from a .txt file by: skogTemp <- read.delim2("Skogaryd_shoot_data.txt", header=TRUE, fill=TRUE) and the data are factors, how can avoid factors from the beginning? Although the file contains both characters and numbers. I tried to convert some of the columns from factor to numeric and as I understood it you can not use only as.numeric but

How do I fix this error ? I tried coercion to a vector but that didn't work. msci <-read.csv("..MSCIexUS.csv", header=TRUE) head(msci) Date index 1 Dec 31, 1969 100 2 Jan 30, 1970 97.655 3 Feb 27, 1970 96.154 4 Mar 31, 1970 95.857 5 Apr 30, 1970 85.564 6 May 29, 1970 79.005 > str(msci) 'data.frame': 510 obs. of 2 variables: $ Date : Factor w/ 510

On 8/23/20 5:02 PM, Rory Winston wrote: > Hi > > I noticed a small inconsistency when using sum() vs cumsum() > > I have a char-based series > > > tryjpy$long > > [1] "0.0022" "-0.0002" "-0.0149" "-0.0023" "-0.0342" "-0.0245" "-0.0022" > > [8] "0.0003" "-0.0001"

Owen Anderson wrote: > > On May 16, 2009, at 7:47 PM, Luke Dalessandro wrote: > >> Also, atomic ops are usually pretty low level things used for >> nonblocking algorithms or to build higher level locking constructs. Is >> that the plan here too? It seems like you'd want to avoid anything too >> fancy since LLVM has to run on so many different architectures

On May 17, 2009, at 5:23 AM, Luke Dalessandro wrote: > Owen Anderson wrote: >> >> On May 16, 2009, at 7:47 PM, Luke Dalessandro wrote: >> >>> Also, atomic ops are usually pretty low level things used for >>> nonblocking algorithms or to build higher level locking >>> constructs. Is >>> that the plan here too? It seems like you'd want

Hi all, The coercion function defined for the ALTREP object will not be called by R when an assignment operation implicitly introduces coercion for a large ALTREP object. For example, If I create a vector of length 10, the ALTREP coercion function seems to work fine. ``` > x <- 1:10 > y <- wrap_altrep(x) > .Internal(inspect(y)) @0x000000001f9271c0 13 INTSXP g0c0 [REF(2)] I am

Hi, I am looking into a way to hook into the R coercion framework to allow me to convert table-like data stored within a COM object into a data.frame. Some of our COM objects have their own table-like data storage, and from R's point of view it's an object (EXTPTRSXP) decoarated with a sepcial symbol so we can easily identify it. COM_Table <- a_method_that_creates_the_object()

Dear ALL I don't know why I can see this error in run this sentences. In paste("V", 1L:cols, sep = "") : NAs introduced by coercion DATA<-read.delim ("D:\\DATA\\GeneExpression.txt",header=FALSE) I will be glad if you help me. Best Regards, Stat Consult [[alternative HTML version deleted]]

At the end of his bug report, Philippe says PhGr> ..... Moreover, the subset operation [] uses as.integer() and PhGr> consequently, can suffer from the same syndrome. A WARNING section in PhGr> Extract.Rd would be welcome too. [BTW: Thank you Philippe! ] Currently, "Extract.Rd" does not say anything on the kind of indices `i' that can be used in things like

I am basically fine with the change. How about using just the following? if(!is.character(exclude)) exclude <- as.vector(exclude, typeof(x)) # may result in NA x <- as.character(x) It looks simpler and is, more or less, equivalent. In factor.Rd, in description of argument 'exclude', "(when \code{x} is a \code{factor} already)" can be removed. A larger

Hi R users I am wondering how I can avoid automatic coercion of my numeric vector elements to character init <- c(age='N', R=as.numeric(0.5), S=as.numeric(0.8)) I have used as.numeric() but it does not seem to work Thank you Lorenzo [[alternative HTML version deleted]]

I work with Windows and use R version 2.4.1. I am JUST starting to learn this program... I get this warning message 'NAs introduced by coercion' while trying to build a distance matrix (to be analyzed with NMDS later) from a 336 x 100 data matrix. The original matrix has lots of zeros and no missing values, but I don't think this should matter. I searched this forum and people have

Hi all, This question has significant potential to be a stupid one, but as I could find no hints in the manual or previous posts: If you have a logical index X: >X [1] TRUE FALSE TRUE TRUE FALSE And you want an equivalent integer index Y: >Y [1] 1 3 4 Is there no easy way? (I'm thinking of the equivalent of FIND in Matlab) Kieran