similar to: rbind error (maybe a problem with chron package?)

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] <-

Dear R help list, I have a plot with two different vertical scales that I want to display on either side of the plot. It's quite similar to the Fahrenheit-Centigrade example in the examples section of the documentation for axis.default. The right-side axis is clipped off, though, and I haven't been able to figure out anything with viewport() and clipping or trellis.par.set to fix

Greetings list, Wondering if anyone has come across this strange dialplan pattern matching issue before: I have a context defined as follows (the plus simply implies it follows on from an existing context in another #include - which, yes, has been included first): [privatedundi](+) exten => _hilton-2XX,1,Goto(hilton,${EXTEN:7},1) When dialling hilton-202 from another box via IAX2, I get:

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

#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",

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,

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

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

On Linux when I compile R 2.10.0(devel) (src/main/arithmetic.c in particular) with gcc 3.4.5 using the flags -g -O2 I get noncommutative behavior when adding NA and NaN: > NA_real_ + NaN [1] NaN > NaN + NA_real_ [1] NA If I compile src/main/arithmetic.c without optimization (just -g) then both of those return NA. On Windows, using a precompiled R 2.8.1 from CRAN I get NA for

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

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 list, I have a list of data frames, in the form (dump output for an example list follows message): $site1 year data 1 2000 0.03685042 2 2001 0.02583885 6 2005 0.02480015 7 2006 0.03458745 $site2 year data 1 2002 4.071134e-03 2 2003 -4.513524e-08 3 2004 8.336272e-08 4 2005 2.270803e-08 5 2006 1.263597e-02 6 2007 NaN I would like to plot each

In R 2.8.0 on Windows (tested both under ESS and under R Console in case there was an I/O issue) There is a bug in printing val <- matrix(list(NA_complex_,NA_complex_),1). > dput(val) structure(list(NA_complex_, NA_complex_), .Dim = 1:2) > print(val) [,1] [1,] [,2] [1,] Note that a large number of spaces are printed instead of NA. Compare the unproblematic real case:

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. >

>>>>> Michael Chirico >>>>> on Sat, 23 May 2020 18:08:22 +0800 writes: > 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

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'

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_?

Hi Michael, I posted something on this topic to R-devel several weeks ago, but never got a response. My ultimate conclusion is that sprintf() isn't super consistent in how it handles coercion: sometimes it'll coerce real to integer without complaint, other times it won't. (My particular email had to do with the vectors longer than 1 and their positioning vis-a-vis the format string.)

Astute observation. And of course we should be passing integer when we use %d. It's an edge case in how we printed ITime objects in data.table: On Tue, May 23, 2017 at 11:53 AM, Joris Meys <jorismeys at gmail.com> wrote: > I initially thought this is "documented behaviour". ?sprintf says: > > Numeric variables with __exactly integer__ values will be coerced to >