similar to: select significant variables

> I am trying to debug a program, and I think tryCatch will help. The > functions involved > process through so many times before I encounter the error, things > are a bit slow to > use debug and browser(). > > I've read the help file and postings on conditions, and am still > having trouble. > > While running my program I am getting a NAN from a called

Dear friends, hope I could be able to explain my problem through following example. Please consider this: > set.seed(1) > input <- rnorm(10) > input [1] -0.6264538 0.1836433 -0.8356286 1.5952808 0.3295078 -0.8204684 0.4874291 0.7383247 0.5757814 -0.3053884 > tag <- vector(length=10) for(i in 1:10) # if there is any ****error**** in evaluating

HI All, I am trying to analyse the results of a heap of samples, to determine how many samples are required to meet a defined confidence interval. I checked out the R manual for bootstrapping and re-sampling methods, but did not find anything. Are there any contributed procedures that deal with this? thanks, Matt Redding Soil Scientist Intensive Livestock Environmental Management-Research

Dear R-experts, I have 28 data points that I would like to fit with a non linear broken-stick -- with three fitted parameters. When I view trace -- and use the final values as lines on the graph of data -- it looks pretty good. Q1. Why am I getting singular convergeance? Q2. Can you suggest another approach that may prove more satisfying? I have read previous examples on nls and this sort of

Dear R useRs, with the following piece of code i try to find the first value which can be calculated without warnings `test` <- function(a) { repeat { ## hide warnings suppressWarnings(log(a)) if (exists("last.warning", envir = .GlobalEnv)) { a <- a + 0.1 ## clear existing warnings rm("last.warning", envir = .GlobalEnv) }

Dear R-Gurus, I have ended up with a calculation problem where I need to use brobs. I have to work my way through a vector with a for loop to act on each element in a calculation (refering to the previous value in the new vector of results -- so as far as I know I can't use "apply") -- this produces a list of brobs. My problem is, how do I act on, plot this list, or do vector

Just to add a note to the question asked by Bill Simpson.. I am confronted with a similar problem, but the model I try to fit on my data is nonlinear. I have a four-parameter, biexponential model describing the response times of a group of subjects performing a set of task. What I want to evaluate is whether the parameter values differ between (groups of) tasks. myfunc <-formula(x ~

I have a problem with duplicated date_time stamps that I do not see as duplicated. I read a file with observations taken every 30 minutes: > aur2009=read.csv(paste(datadir,"AUR_ECPP_2009.csv",sep="/"),sep=";",stringsAsFactors=F) > aur2009[1:3,1:5] Date.Time E_filled E_filled_flag LE_filled LE_filled_flag 1 1/1/2009 0:00 0 NaN 5.86

Hi Craig, On 03.07.19 17:33, Craig Topper wrote: > Don't the CreateICmp calls return a Value* with an i1 type? But then > they are added to an i8 type? Not sure that works.  I had that initially: auto cf = IRB.CreateICmpULT(Incr, ConstantInt::get(Int8Ty, 1)); auto carry = IRB.CreateZExt(cf, Int8Ty); Incr = IRB.CreateAdd(Incr, carry); it makes no difference to the generated assembly

Hello, I have an optimisation issue in an llvm IR pass - the issue being that unnecessary instructions are generated in the final assembly (with -O3). I want to create the following assembly snippet: mov dl,BYTE PTR [rsi+rdi*1] add dl,0x1 adc dl,0x0 mov BYTE PTR [rsi+rdi*1],dl however what is created is (variant #1): mov dl,BYTE PTR [rsi+rdx*1] add dl,0x1 cmp

moments::anscombe.test(x) does give errors when x has too few values or if all the values in x are the same > moments::anscombe.test(c(1,2,6)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed > moments::anscombe.test(c(2,2,2,2,2,2,2,2)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed You can use tryCatch() to

Hi Bill, Thanks for prompt reply and letting me know a way around it. I have more than 1200 observations and not all the values are the same. However, my data points are quite similar, for example, 0.079275, 0.078867, 0.070716 in millions and etc. I have run the data without converting it to millions and I still get the same error message. As I have kurtosis value, it should be fine for the

Hi all, While running the anscombe.test in R, I'm getting an error of *Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed* for a few time series columns whereas for most of the series the function is working fine. I have checked for those specific columns for missing values. However, there is no NA/NAN value in the dataset. I have also run kurtosis for

Hi, For the program below, where "incr" and "Arr" are globals ================================= int incr; float Arr[1000]; int foo () {   float x = 0;   int newInc = incr+1;   for (int i = 0; i < 1000; i++) {     for (int j = 0; j < 1000; j += incr) {         x += (Arr[i] + Arr[j]);     }   }   return x; } ================================= The SCEV expression computed

I am trying to use the dmt function in the package {mnormt}. Throughout my algorithm, the covariance matrix is sometime calculated to be singular. When attempting to calculate the dmt function with a covariance that is not positive definite, I would like it to return Inf or NaN instead of an error message. I have been using the try function, however it is not yeilding the desired result. (I did

Full_Name: Wolfgang Resch Version: R 2.8.1 GUI 1.27 OS: OS X 10.4.11 Submission from: (NULL) (137.187.89.14) Strange behavior of qbinom: > qbinom(0.01, 5016279, 1e-07) [1] 0 > qbinom(0.01, 5016279, 2e-07) [1] 16 > qbinom(0.01, 5016279, 3e-07) [1] 16 > qbinom(0.01, 5016279, 4e-07) [1] 16 > qbinom(0.01, 5016279, 5e-07) [1] 0

Hi R sages, Here is my latest problem. Consider the following toy example: x <- read.table(textConnection("y1 y2 y3 x1 x2 indv.1 bagels donuts bagels 4 6 indv.2 donuts donuts donuts 5 1 indv.3 donuts donuts donuts 1 10 indv.4 donuts donuts donuts 10 9 indv.5 bagels donuts bagels 0 2 indv.6 bagels donuts bagels 2 9 indv.7 bagels donuts bagels 8 5 indv.8 bagels donuts bagels 4 1 indv.9

Hi I am a newbie to R and am using the lm function to fit my data. This optimization is to be performed for around 45000 files not all of which lend themselves to optimization. Some of these will and do crash. However, How do I ensure that the program simply goes to the next file in line without exiting the code with the error "Error in lm.fit(x, y, offset = offset, singular.ok =

Hello, I tried this pseudo-generator style experiment (see below). The "<<-" operator assigns to in the calling environment which would be the environment of "getN". Yet when the function incr is returned, isn't this environment lost? Also the print displays GlobalEnv, yet the globalenv does not have any mention of startgiven. This code was inspired from and old

Hi All, I've been trawling through the documentation and listserv archives on this topic -- but as yet have not found a solution. I'm sure this is pretty simple with R, but I cannot work out how without resorting to ugly nested loops. As far as I can tell, grep, match, and %in% are not the correct tools. Question: given these vectors -- patrn <- c(1,2,3,4) exmpl <-