similar to: R-beta: NaN & Inf: Thanks for your quick help

Can someone explain what this words (NaN and Inf) mean ? I get then as a result of some matrix operations, in the end I have a matrix without any figures just this words. regards ernesto ______________________________________________________ Get Your Private, Free Email at http://www.hotmail.com -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

Hi, I want to recode all Inf and NaN values to NA, but I;m surprised to see the result of the following code. Could anybody enlighten me about this? > df <- data.frame(a=c(NA, NaN, Inf, 1:3)) > df[is.infinite(df) | is.nan(df)] <- NA > df a 1 NA 2 NaN 3 Inf 4 1 5 2 6 3 > Thanks! Cheers!! Albert-Jan

Hi, I want to recode all Inf and NaN values to NA, but I;m surprised to see the result of the following code. Could anybody enlighten me about this? > df <- data.frame(a=c(NA, NaN, Inf, 1:3)) > df[is.infinite(df) | is.nan(df)] <- NA > df a 1 NA 2 NaN 3 Inf 4 1 5 2 6 3 > Thanks! Cheers!! Albert-Jan

Hi everyone, I use the boot package within the MBESS package to automate much of the hard part for folks interested in performing a (simple) mediation model. The function mediation() works well, except for a (probably) unrealistic artificial data set. When I apply the bootstrap I sometimes get: Error in t.star[r, ] <- res[[r]] which is (I think) due to Inf and -Inf and NaN values produced for

Dear all, I have a datafile where I run haplo.GLM analyses using several variables (a matrix). However, when I include a certain binary variable (0,1) I get this message Error: NA/NaN/Inf in foreign function call (arg 4) I don't get an error when I include another binary variable, again with only 0,1. Both variables don't have missing values, they only have 0 and 1. Why do I get an

In R, 0 ^ NaN yields Inf. I would have expected NaN or perhaps 0. Is this behaviour intended? >sessionInfo() R version 2.8.0 (2008-10-20) i386-pc-mingw32 locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grDevices utils

Hi all.. I'm very new R, and i'm analyzing microarray data using Bioconductor.. Recently i was given microarray data to analyze. The problem is whenever i run MAS5 presence calls algorithm, it throws an error saying NA/NaN/Inf in foreign function. How do i remove such NA/NaN/Inf's ?? I tried na.omit(dataframe) but stil problem exists. dimension of matrix (data) is 35556 7. >

Full_Name: G?ran Brostr?m Version: 2.3.1 OS: Linux, ubuntu Submission from: (NULL) (85.11.40.53) > dweibull(0, 0.5, 1) [1] NaN Warning message: NaNs produced in: dweibull(x, shape, scale, log) should give Inf (and no Warning). Compare with > dgamma(0, 0.5, 1) [1] Inf This happens when 'shape' < 1.

Under windows, R supports IEEE floating point arithmetic, but doesn't allow conversion of Inf and NaN from character to numeric. R> is.nan(NaN) [1] TRUE R> as.numeric(as.character(NaN)) [1] NA Warning message: NAs introduced by coercion R> is.infinite(Inf) [1] TRUE R> as.numeric(as.character(Inf)) [1] NA Warning message: NAs introduced by coercion whereas under Linux R>

I am attempting to fit discrete data (daily counts of arrivals of recreational vessels at locks on a river) using the fit.dist package. Some distributions return values of NaN and Inf for certain situations, an example with Inf values is shown below. # of vessels: 1 2 3 4 5 6 7 8 9 10 11 # of days with # of vessels: 35 20 10 5 6

Hello, I am new with R, and I'm trying to fit a linear model, I did the following and obtein this result, can anybody help? Thanks, > logdftodos7925vi <- log(dftodos7925vi) > logALTURA7925<- log(dftodos7925$ALTURA7917) > logtodos7925.lm <- lm (logALTURA7925~., data= logdftodos7925vi) Error en lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : NA/NaN/Inf en

I stumbled across this and I am wondering if this is unexpected behavior or if I am missing something. > pnorm(-1.0e+307, log.p=TRUE) [1] -Inf > pnorm(-1.0e+308, log.p=TRUE) [1] NaN Warning message: In pnorm(q, mean, sd, lower.tail, log.p) : NaNs produced > pnorm(-1.0e+309, log.p=TRUE) [1] -Inf I don't know C and am not that skilled with R, so it would be hard for me to look into

Dear all, I try to fit a glmmPQL on a huge data with 384189 individuals id=1:384189: working in 1520 establishments est:1:1516. The minimum number of individuals in every establishment is 30. This works for a subsample excluding establishemnet cells smaller than 100, but fail when we include smaller cells: R> summary(glmmPQL(count ~ + I( age-ave(age,est) )* ave(age,est) + + I(

Hi, I have a huge data table with several variables containing missing values. I want to make a simple scatter plot (Mass, HSI) and draw a smooth regression on it. Here are the summaries of these two variables: > summary(Mass) Min. 1st Qu. Median Mean 3rd Qu. Max. 46.0 205.9 272.5 282.6 348.3 610.1 > summary(HSI) Min. 1st Qu. Median Mean 3rd Qu. Max.

I am trying to use knn to do a nearest neighbor classification. I tried using my dataset and got an error message so I used a simple example to try and understand what I was doing wrong and got the same message. Here is what I typed into R: try [,1] [,2] [,3] [,4] r "A" "A" "T" "G" r "A" "A" "T" "G" f

I'm using glmmPQL, and I still have a few problems with it. In addition to the issue reported earlier, I'm getting the following error and I was wondering if there's something I can do about it. Error in logLik.reStruct(object, conLin) : Na/NaN/Inf in foreign function call (arg 3) ... Warnings: 1: Singular precistion matrix in level -1, block 4 (...) 4: "" The

I am conducting a simulation study generating multivariate normal data, deleting observations to create a data set with missing values and then using multiple imputation via da.norm in Schafer's norm package. >From da.norm, I get the following error message: "Error: NA/NaN/Inf in foreign function call (arg 2)" The frequency of the error message seems to depend on the ratio of n

Dear R-helpers: I am trying to fit a multivariate Cox proportional hazards model, modelling survival outcome as a function of treatment and receptor status. The data look like below: # structure of the data str(sample.data) List of 4 $ survobj : Surv [1:129, 1:2] 0.8925+ 1.8836+ 2.1191+ 5.3744+ 1.6099+ 5.2567 0.2081+ 0.2108+ 0.2683+ 0.4873+ ... ..- attr(*, "dimnames")=List of 2

Hi - First posting here. I am using fPortfolio to try and optimize a simple portfolio consisting of 5 daily return series. I want to maximize return subject to setTargetRisk(myspec)=0.08 using only constraints="LongOnly" I can run feasiblePortfolio() using a spec file that specifies the weights, and it works fine. When I run maxreturnPortfolio(mydata,myspec,"LongOnly"),

Hi all, I'm new to R and I'm struggling to decipher an error message. Briefly, I am trying to use the pvclust package to do hierarchical clustering of some CGH data. The data is from the Progenetix CGH database. It is arranged as a table where each column is a single case and each row is a single chromosome band. The value in each cell is either 0, 1, 2, or -1. Corresponding to no change,