similar to: (PR#7824) handling of zero and negative indices in

This message contains a description of what looks like a bug, examples of the suspect behavior, a proposed change to the C code to change this behavior, example of behavior with the fix, and suggestions for 3 places to update the documentation to reflect the proposed behavior. It is submitted for consideration for inclusion in R. Comments are requested. Currently, the code for subscripting

I found a bug in one of the fourteen speed patches I posted, namely in patch-vec-subset. I've fixed this (I now see one does need to duplicate index vectors sometimes, though one can avoid it most of the time). I also split this patch in two, since it really has two different and independent parts. The patch-vec-subset patch now has only some straightforward (locally-checkable) speedups for

Matrix indexing seems to give rather "variable" results when zeros or negative values are included among the indices (in terms of both error messages and in terms of the number of returned values when there is no error message). Is this the intended behavior? I couldn't see any comments about zeros or negative values in matrix indices in either ?"[" or Section 3.4.2

For block effects with small variance, lmer will sometimes estimate the variance as being very close to zero and issue a warning. I don't have a problem with this -- I've explored things a bit with some simulations (see below) and conclude that this is probably inevitable when trying to incorporate random effects with not very much data (the means and medians of estimates are plausibly

The sapply function is refusing to return a result for what seem to me to be mysterious reasons. Here is a toy example: set.seed(111) X <- list(x=runif(20),y=runif(20)) rvec <- seq(0.01,0.15,length=42) foo <- function(x,X,cc) { mean((X$x)^x + (X$y)^cc) } bar <- function(x,a,b){a+b*x} try.b <- sapply(rvec,bar,a=1,b=2) # This runs without a problem and

Dear R-Developers, I think I found two bugs in max.col(). Ties between zeros are not broken, which might affect simulations. -Inf and Zero can be treated the same, which can give completely wrong results, e.g. when the second max is sought by replacing all maxs by -Inf. To fix max.col I do offer the C-code behind my function rowMax(), which also handles NAs and seems to be faster. However,

Factor out all kernel specific path's (those containing usr/) into two variables: KLIBSRC + KLIBINC. Set the variables in a kernel spcific Kbuild file. Sam commit e6f989c1597a837f4aecbd11083697184c089611 tree 93f88d7564bb9e4d4bc95fd455b842d0bd0fdc54 parent 8151f4a98f82fba4fe3b949f49da4ab8bba71501 author Sam Ravnborg <sam@mars.(none)> Thu, 28 Jul 2005 23:36:07 +0200 committer Sam

GEN usr/klibc/syscalls/SYSCALLS.i GEN usr/klibc/syscalls/syscalls.nrs GEN usr/klibc/syscalls/typesize.c KLIBCCC usr/klibc/syscalls/typesize.o OBJCOPY usr/klibc/syscalls/typesize.bin GEN usr/klibc/syscalls/syscalls.mk GEN usr/klibc/syscalls/SYSCALLS.i GEN usr/klibc/syscalls/syscalls.nrs GEN usr/klibc/syscalls/typesize.c KLIBCCC

Hi, Was wondering if anyone had any tips or experience in getting a Nortel CS1K and Asterisk 1.4.19 to talk to each other via NRS? So far I've gotten asterisk to place calls to the CS1k via the NRS, however calls originated by the CS1K get rejected by the NRS with a 404 Not Found message. If I take the NRS out of the equation by replacing the IP address of the NRS in the CS1K with that

Hello, I have a problem writing a variable to an existing file. Below is a part of my script and how it fails. I can't find "create.var.ncdf" in help Thanks for any help. Mark nc <- open.ncdf(ncname, readunlim=FALSE, write=TRUE ) missing <- 1.e+30 xdim <- nc$dim[["west_east"]] ydim <- nc$dim[["south_north"]] tdim <- nc$dim[["Time"]]

Dear CSAG R users, I will be glad if someone can point out what I am doing wrong or not doing at all in this. I am trying to write out netcdf file in R. I have 26 time step but only the first time step is written. For example: >library(ncdf) >path <- '/home/work/' >forecast <- open.ncdf(paste(path,'cam.1980.2005.nc',sep="")) > fore <-

Dear CSAG R users, I will be glad if someone can point out what I am doing wrong or not doing at all in this. I am trying to write out netcdf file in R. I have 26 time step but only the first time step is written. For example: >library(ncdf) >path <- '/home/work/' >forecast <- open.ncdf(paste(path,'cam.1980.2005.nc',sep="")) > fore <-

Hi, I'm running the following code to produce lattice plots of microfibril angle versus ring number in Scots pine. There are 12 trees and 5 sample positions ("Position") in each tree: xyplot(MFA ~ RN | Tree, data = MFA.data, groups = Position, subscripts=TRUE, auto.key=list(space = "top", points = FALSE, lines = TRUE, reverse.rows=TRUE,

What do I need to do to fix this? [jonsmirl@smirl klibc-0.184]$ make make[1]: Entering directory `/home/dri/klibc-0.184/klibc' gcc -Wp,-MT,syscalls.nrs,-MD,./.syscalls.nrs.d -mregparm=3 -DREGPARM=3 -march=i386 -Os -g -falign-functions=0 -falign-jumps=0 -falign-loops=0 -nostdinc -iwithprefix include -D__KLIBC__ -DBITSIZE=32 -I../include/arch/i386 -I../include/bits32 -I../include

I have a VAR model with five macro-economic variables, y[1], y[2], y[3], y[4], y[5]. They are related to each other in following manner. y[1,t] = alpha[1,0] + beta[1,1, 1]*y[1,t-1]+............+beta[1,1, 12]*y[1,t-12] + beta[1,2, 1]*y[2,t-1]+............+beta[1,2, 12]*y[2,t-12] + e[1,t] y[2,t] = alpha[2,0] + beta[2,2, 1]*y[2,t-1]+............+beta[2,2, 12]*y[2,t-12] + e[2,t] y[3,t] = alpha[3,0]

Hi there I'm trying to find the mle fo a multinomial model ->*L(N,h,S?x)*. There is only *N* I want to estimate, which is used in the number of successes for the last cell probability. These successes are given by: p^(N-x1-x2-...xi) All the other parameters (i.e. h and S) I know from somewhere else. Here is what I've tried to do so far for a imaginary data set:

R-devel: Some very inconsistent behavior, that I can't seem to find documented. Sys.setenv(TZ="GMT") str(unclass(strptime("1969-12-31 23:59:59","%Y-%m-%d %H:%M:%S"))) List of 9 $ sec : num 59 $ min : int 59 $ hour : int 23 $ mday : int 31 $ mon : int 11 $ year : int 69 $ wday : int 3 $ yday : int 364 $ isdst: int 0 - attr(*, "tzone")= chr

Hello all, I posted the following bug last week: # These calls work correctly: match(c("A", "B", "C"), c("A","C"), incomparables=NA) # okay match(c("A", "B", "C"), "A") # okay match("A", c("A", "B"), incomparables=NA) # okay # This one causes R to hang: match(c("A",

Dear R-Helpers, I would like to know what syntax I need to use to do a nested anova for 1. a continuous variable and 2. count data (x out of y) 1. The first I used to do in SPSS and I would like to be able to do it in R as well. This is the hierarchical model I would like to use: a continuous variable explained by factor A(fixed) + factor B(random) nested in A + factor C (random) nested in

Doug, I thought perhaps that you might be interested in the comparison of lme to the results for the same models fitted by Richard Jones' carma (I just wrote the R interface to his Fortran code). The code to run the example from the lme help and for the equivalent with carma is in the file below. The two main differences in results are 1. the random coefficients covariance matrix is quite