similar to: range function with finite=T and logical parameters

>>>>> Lukas Stadler <lukas.stadler at oracle.com> >>>>> on Mon, 23 Oct 2017 15:56:55 +0200 writes: > Hi! > I was wondering about the behavior of the range function wrt. logical NAs: >> range(c(0L, 1L, NA), finite=T) > [1] 0 1 >> range(c(F, T, NA), finite=T) > [1] NA NA > The documentation is quite

The build system rolled up R-3.4.3.tar.gz (codename "Kite-Eating Tree") this morning. The list below details the changes in this release. You can get the source code from http://cran.r-project.org/src/base/R-3/R-3.4.3.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. For the R Core Team, Peter Dalgaard

The build system rolled up R-3.4.3.tar.gz (codename "Kite-Eating Tree") this morning. The list below details the changes in this release. You can get the source code from http://cran.r-project.org/src/base/R-3/R-3.4.3.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. For the R Core Team, Peter Dalgaard

Thanks: I installed from source and got an error when loading a package: -------------------------------------------------------------------- > library(eha) Loading required package: survival Error: package or namespace load failed for ?eha? in dyn.load(file, DLLpath = DLLpath, ...): unable to load shared object '/usr/local/lib/R/site-library/eha/libs/eha.so':

A tiny nit-pick: Seems to me that end date = NA would mean the event has not yet ended, whilst Inf would mean that the event is known to never terminate, ie: an eternal fact, or physical law. On Fri, Apr 28, 2023 at 10:12?AM Davis Vaughan via R-devel < r-devel at r-project.org> wrote: > Hi all, > > I noticed that `range.default()` has a nice `finite = TRUE` argument, > but it

Hi all, I noticed that `range.default()` has a nice `finite = TRUE` argument, but it doesn't actually apply to Date or POSIXct due to how `is.numeric()` works. ``` x <- .Date(c(0, Inf, 1, 2, Inf)) x #> [1] "1970-01-01" "Inf" "1970-01-02" "1970-01-03" "Inf" # Darn! range(x, finite = TRUE) #> [1] "1970-01-01"

Hi, there was a change concerning logical operations about a year ago: https://github.com/wch/r-source/commit/9e19d3e3dd5f657b5cfefe562bdd7ede2e2b8786 It's related to a discussion on this list: https://hypatia.math.ethz.ch/pipermail/r-devel/2016-September/073068.html <https://hypatia.math.ethz.ch/pipermail/r-devel/2016-September/073068.html> A change in logic.c:134 influences the

Hi All, I think there may be some possible confusion about what allowsInf would be reporting (or maybe its just me :) ) if we did this. Consider a class "myclass", S3, for starters, with setMethod("allowsInf", "myclass", function(obj) FALSE) Then, what would myclassthing <- structure(1.5, class = "mything") myclassthing[1] <- Inf do. Assumely it

?typeof? is your friend here: > typeof(`[`) [1] "special" > typeof(mc[[1]]) [1] "symbol" > typeof(mc2[[1]]) [1] "special" so mc[[1]] is a symbol, and thus not a primitive. - Lukas > On 28 Mar 2017, at 14:46, Michael Lawrence <lawrence.michael at gene.com> wrote: > > There is a difference between the symbol and the function (primitive >

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I think there?s a bug concerning the formatting of raw vectors with names: > structure(as.raw(1:3), .Names = c("a", "bbbb", "c")) a bbbb c 01 02 03 > structure(1:3, .Names = c("a", "bbbb", "c")) a bbbb c 1 2 3 The problem is that EncodeRaw does not honor the requested width, in fact it doesn?t even get the

Hi! We?ve seen a problem with the compiler in specific cases of matrix updates: > { m <- matrix(1:4, 2) ; z <- 0; for(i in 1) { m[z <- z + 1,z <- z + 1] <- 99; } ; m } [,1] [,2] [1,] 1 3 [2,] 2 99 Here, it modifies element [2,2], which is unexpected. It behaves correct without the loop: > { m <- matrix(1:4, 2) ; z <- 0; m[z <- z + 1,z <- z + 1]

Hi! We?ve recently come across an example where a package (minqa) creates an Rcpp Function object in a static variable. This causes R_ReleaseObject to be called by the destructor at a very late point in time - as part of the system exit function: static Function cf("c"); I?m wondering if that is considered to be ?safe?? Is the R engine supposed to stay in a state where calls to API

Hi! I noticed that cumsum behaves different than the other cumulative functions wrt. NaN values: > values <- c(1,2,NaN,1) > for ( f in c(cumsum, cumprod, cummin, cummax)) print(f(values)) [1] 1 3 NA NA [1] 1 2 NaN NaN [1] 1 1 NaN NaN [1] 1 2 NaN NaN The reason is that cumsum (in cum.c:33) contains an explicit check for ISNAN. Is that intentional? IMHO, ISNA would be better

> ?is.finite `is.finite' and `is.infinite' return a vector of the same length as `x', indicating which elements are finite or not. is.finite() of a list seems to return a vector of the length of the list, but with value FALSE if any list element isn't finite. Is this intended? > l4 <- list(NA,1,2,3); l4; length(l4); is.finite(l4) [[1]] [1] NA [[2]] [1] 1

Dear R-helpers, running a zeroinflated model of the following type: zinb = zeroinfl(count=response ~., x = ~ . - response, z = ~. - response, dist = "negbin", data = t.data, trace = TRUE) generates the following message: Zero-Inflated Count Model Using logit to model zero vs non-zero Using Negative Binomial for counts dependent variable y: Y 0 1 2 3 359 52 7 3 generating

Hi list! I'm getting an error message when trying to fit an accelerated failure time parametric model using the aftreg() function from package eha: > Error in optim(beta, Fmin, method = "BFGS", control = list(trace = > as.integer(printlevel)), : > non-finite finite-difference value [2] This only happens when adding four specific covariates at the same time in the

Dear R users, I have a question about numerical integration in R. I am facing the 'non-finite function value' error while integrating the function xf(x) using 'integrate'. f(x) is a probability density function and assumed to follow the three parameter (min = 0) beta distribution for which I have estimated the parameters. The function is integrated

Hello, I'm trying to use fitdistr() from the MASS package to fit a gamma distribution to a set of data. The data set is too large (1167 values) to reproduce in an email, but the summary statistics are: Min. 1st Qu. Median Mean 3rd Qu. Max. 116.7 266.7 666.7 1348.0 1642.0 16720.0 The call I'm trying to make is: fitdistr(x,"gamma") and the error is: Error in optim(x =

Dear R-help, I am doing clustering via finite mixture model. Please suggest some packages in R to find clusters via finite mixture model with continuous variables. And also I wish to verify the distributional properties of the mixture distributions by fitting the model with lognormal, gamma, exponentials etc,. Thanks in advance,  warm regards,Ms.Karunambigai M PhD Scholar Dept. of Biostatistics