similar to: NA_real_ <op> NaN -> NA or NaN, should we care?

Hi all, I am currently compiling R to RISC-V64 CPU and I think I have discovered a NA propagation failure. How R implements NA (not available) and NaN (not-a-number) is explained in detail here: https://stat.ethz.ch/pipermail/r-devel/2014-February/068380.html. In short, according to my understanding of R's convention, any calculation involving NA but no NaN should result in NA (called NA

Hi all, Surprisingly (at least to me), `as.complex(NA_real_)` results in `complex(real = NA_real_, imaginary = 0)` rather than `NA_complex_`. It seems to me that this goes against the docs of `as.complex()`, which say this in the Details section: "Up to R versions 3.2.x, all forms of NA and NaN were coerced to a complex NA, i.e., the NA_complex_ constant, for which both the real and

This is a great example how you cannot figure it out after spending two hours troubleshooting, but a few minutes after you post to R-devel, it's just jumps to you (is there a word for this other than "impatient"?); Let me answer my own question. The discrepancy between my sum2() code and the internal code for base::sum() is that the latter uses LDOUBLE = long double (on some system

Hello R community, I am attempting to run multiple logistic regressions (multinomial, via package 'nnet'), with Automated Model Selection (dredge, package 'MuMIn'). The aim is to reduce the number of predictor variables by assessing relative performance of each variable, which can be done in a coarse fashion using the Automated Model Selection option in package 'MuMIn'

I'm observing that base::sum(x, na.rm=FALSE) for typeof(x) == "double" is much more time consuming when there are missing values versus when there are not. I'm observing this on both Window and Linux, but it's quite surprising to me. Currently, my main suspect is settings in on how R was built. The second suspect is my brain. I hope that someone can clarify the below

The thread "Problems with kernel-3.10.0-693.5.2.el7.x86_64? reminded me that I have a similar problem but on the latest CentOS 6 kernel I?ve been meaning to report. Here is the relevant system information: Linux ssg003.bose.com 2.6.32-696.13.2.el6.i686 #1 SMP Thu Oct 5 20:42:25 UTC 2017 i686 i686 i386 GNU/Linux 00:02.0 VGA compatible controller: Intel Corporation Device 5912 (rev 04)

Am I the only one seeing this issue? Or is it that so few people are still running CentOS 6.x? Quick summary, on a very recent Dell motherboard using the on-board vide and booting the latest CentOS 6 kernel with the ?vga=xxx? parameter set to any non-default value results in unusable X11 graphics. Alfred > On Oct 29, 2017, at 15:29, Alfred von Campe <alfred at von-campe.com> wrote:

Anything else I can provide ?? Sent from my Sprint Samsung Galaxy S7. -------- Original message --------From: Larry Rosenman <larryrtx at gmail.com> Date: 11/1/16 1:37 PM (GMT-06:00) To: Aki Tuomi <aki.tuomi at dovecot.fi> Cc: Dovecot Mailing List <dovecot at dovecot.org> Subject: Re: doveadm index: can't index a different namespace? Nothing in them from what I can

I am trying to set up a data set for a survival analysis with time-varying covariates. The data is already in a long format, but does not have a variable to signify the stopping point for the interval. The variable DaysEnrolled is the variable I would like to use to form this interval. This is what I have now: ID Age DaysEnrolled HAZ WAZ WHZ Food onARV

Hello, I have the following loop for two data sets: diveData_2008 and diveData_2009. It uses two other data: diveCond_all and fishTable. The problem is at the point to identify the dive_id for the given index (index is timestamp). It keeps on saying for the1st loop Error in fishReport$dive_id[i] <- dive_id : replacement has length zero for the 2nd loop Error in fishReport$dive_id[i + j] <-

#is there a way to get NA in the table of descriptive statistics instead of the function stopping Thank you in advance #data x.f <- structure(list(Site = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("BC", "HC", "RM119", "RM148", "RM179", "RM185",

Hello, I?m sending doveadm ?kick? commands to doveadm-server via the doveadm protocol. When ?kick? sends back a NOTFOUND error, though, it?s sending back additional output. strace shows: write(3<UNIX:[3158354->3156665]>, "\t\tkick\tmyssltest\n", 17) = 17 ... read(3<UNIX:[3158354->3156665]>, "\n-NOTFOUND\n\n-\n", 8192) = 14 Going by the protocol

I'm trying to plot smooth trend using smoothTrend in OpenAir but I'm having problems. I used the following code. --------------------------------------------------------------------------------- #Set my working dir to the dir with my files setwd("c:/R") #Load the openair library library(openair) #Load the data mydata <- read.table("MCNP-pH.csv", header=TRUE,

doveadm -D -vvvvvv index \#ARCHIVE/\* garners the below for ALL mailboxes in the namespace: doveadm(ler): Error: Mailbox #ARCHIVE/2013/04/clamav-rules: Status lookup failed: Internal error occurred. Refer to server log for more information. [2016-11-01 13:25:21] doveadm(ler): Error: lucene: Failed to sync mailbox INBOX: Mailbox isn't selectable doveadm(ler): Error: Mailbox

merge can only merge two objects at a time- I would like to merge more than two objects at a time. s.d <- structure(list(RiverMile = c(202L, 198L, 190L, 185L, 179L, 148L, 119L, 61L)), .Names = "RiverMile", row.names = c(NA, -8L), class = "data.frame") #s.d is all of the river miles that can occur in all of the data frames that I want to put together feb06 <-

Dear R Team The following line returns 0 (zero) as answer: sum(c(NA_real_, NA_real_, NA_real_, NA_real_), na.rm = TRUE) One would, however, have expected it to return 'NaN', as is the case with function 'mean': > mean(c(NA_real_, NA_real_, NA_real_, NA_real_), na.rm = TRUE) [1] NaN The problem in other words: I have a vector filled with missing numbers. I run the

This is an example of two months of data from a twenty four month data set that I would like to apply this too. These data are subsets of the same stations throught time, but differing ones were included on different sampling dates. I would like to subset these data and then put them together as a big matrix with the by column being RiverMile. What is the easiest way to proceed as this is a

Hello, I have a list of data frames that I would like to combine to a single data frame. I typically do this with: do.call(rbind, list.of.dataframes) This time, I get Error in class(x) <- cl : cannot set class to "array" unless the dimension attribute has length > 0 I'm not sure what's happening. Each data frame has a column of chron objects and a column of float

I don't see this specific case documented anywhere (I also tried to search the r-devel archives, as well as I could); the only close reference mentions NA & FALSE = FALSE, NA | TRUE = TRUE. And there's also this snippet from R-lang: In cases where the result of the operation would be the same for all > possible values the NA could take, the operation may return this value. >

Consider #as.numeric for emphasis sprintf('%d', as.numeric(1)) # [1] "1" vs. sprintf('%d', NA_real_) > Error in sprintf("%d", NA_real_) : invalid format '%d'; use format %f, %e, %g or %a for numeric object > I understand the error is correct, but if it works for other numeric input, why doesn't R just coerce NA_real_ to NA_integer_?