similar to: FW: error predicting values from the LME

I'm trying to apply a function defined in the VW R docs, that attemps to convert a data.table object to Vowpal Wabbit format. In the process i'm getting the error in printf mentioned in the subject. The original function is here: https://github.com/JohnLangford/vowpal_wabbit/blob/master/R/dt2vw.R Below there is a small example that reproduces the error. The function works great with

Hi all, I have some trouble reading data from a csv file. I used command "read.delim("clipboard") to read in the data. > aalpha.data <- read.delim("clipboard") > class(aalpha.data) [1] "data.frame" > dim(aalpha.data) [1] 8 25 > colnames(aalpha.data) [1] "X" "V1" "V2" "V3" "V4"

Hi, I'm having a problem using sample() within a function. Basically I get an error reading: Error in sample(v, 1, prob = h) : non-positive probability Can anyone advise me as to the possible origin of this error? Here is my code #Discretised Gillespie algorithm function (From SMfSB, D.J. Wilkinson) gillespied=function (N, T=100, dt=1, ...) { tt=0 n=T%/%dt x=N$M

Hi. I have a simple (I think) question My dataset have these variables: names(data) [1] "v1" "v2" "v3" "v4" "v5" "v6" "v7" "v8" "v9" "v10" "v11" "v12" "v13" "v14" "v15" "v16" "v17"

Wouldn't it make sense to have this in the man page? The 8192-byte limitation for 'fmt' is mentioned but not this one. Thanks, H. On 08/25/2015 02:08 AM, Prof Brian Ripley wrote: > From the sources: > > #define MAXNARGS 100 > /* ^^^ not entirely arbitrary, but strongly linked to > allowing %$1 to %$99 !*/ > > > > On 22/08/2015 04:21, Martin

Hello all, I'm trying to create a 2x2 matrix, 32 times after unlist() so that I can convert the list to matrix. I've looked through the R archive but couldn't find the answer. There is what I've done. > f <- system("ls *.txt", intern=TRUE) > x <- lapply(f, read.table) > x [[1]] V1 V2 1 -27.3 14.4 2 29.0 -38.1 [[2]] V1 V2 1 14.4

Dear All I want to chose just spacial columns in R. (read table) data1<- read.table("/home/Documents/data.txt",header=F,sep = "\t", as.is =F) data.2<-data1[sub.data[,1],] The dimension of data.2 is correct but my data are transformed NA head(data.2) V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21 V22 V23 V24 NA <NA> NA NA NA

Hello, I am trying to select the following headers from a data frame but when I try and run the command it executes halfway through and give me an error at V188 and V359. Temp <- data.frame(V4, V5, V6, V7, V8, V9, V10, V11, V12, V13, V14, V15, V16, V17, V18, V19, V20, V21, V22, V23, V24, V25, V26, V27, V28, V29, V30, V31, V32, V33, V34, V35, V36, V37, V38, V39, V40, V41, V42, V43, V44, V45,

Hi All I was wondering how to get the same results with gls and lme. In my lme, the design matrix for the random effects is (should be) a identity matrix and therefore G should add up with R to produce the R matrix that gls would report (V=ZGZ'+R). Added complexity is that I have 3 levels, so I have R, G and say H (V=WHW'+ZGZ'+R). The lme is giving me the correct results, I am

Hello, I am trying to construct two matrices, F and V, composed of partial derivatives and then find the eigenvalues of F*Inverse(V). I have the following equations in ryacas notation: > library(Ryacas) > FIh <- Expr("betah*Sh*Iv") > FIv <- Expr("betav*Sv*Ih") > VIh <- Expr("(muh + gamma)*Ih") > VIv <- Expr("muv*Iv") I

Hello, I have a question and need your help urgently. I am new to R but want to learn it. I have several files in a folder which I have imported to R using : temp = list.files(pattern="*.txt") >myfiles = lapply(temp, read.delim) The resulting files are on the workspace stored as List[110]. So they are 110 files in the list. Each file has several different columns and rows. My

Dear R gurus, Thank you all for continuous support and guidance -- learning without you would not be efficient. I have a question regarding LD analysis and how to best code it up in R. I have a file of (V52 and 671 time points across all columns) and another file of phonetic features (each vowel is aligned with a distinct binary sequence, i.e. E 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0

Hello R-Users, its again me with a question. I´m using R 2.5.0 on Mac Power Book running Mac OS X 10.4.10 I try to calculate distances betweeen two data tables looking like this V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21 V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 1 1 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0 0 1 0 0

Hello, Why do I get preceding "X." (that is a and X followed by a period) for negative numbers and an "X" for positive numbers when I read a csv file? Am I stuck with this? If so, how do I convert it to normal numbers? dat=read.csv(file_path) > dat [1] X0.0 X.0.240432350374 X0.355468069625 X.0.211469972378 X1.1812797415 X.0.227975150826

Hi, I am trying to use a mantel test on two distance matrices. The code I have entered for each is: Gen_dists <- read.csv(file.choose(), stringsAsFactors = FALSE, na.strings = c(" "), fill = T,

Hi every one I?m new to R and I cant figure our how to use the loop to do the following task, any help would be very kind of every one. I have a file called (table3.txt) that contains over 1000 row and over 40 columns. So for example first row would look like that Deafness, EYA4, DIAPH1, MYO7A, TECTA, COL11A2, POU4F3, MYH9, ACTG1, MYO6 I want the loop stamens to loop thro each row

Dear List I have a fixed width file with variables of varying width. The help is pretty transparent for this feature, but I can't seem to figure out how I can make effective use of the package with my data. In my dataset, the first 80 columns are of width 1 followed by other variables with width larger than 1. I think the correct way to do this, by brute force, would be >

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Dear R community, I have trouble implementing a nested variance-covariance matrix in the lme function. The model has two fixed effects called End and logpgc, the response variable is the logarithm to base 2 of Intensity ( log2(Intensity) ) and the random effects are called Probe and ProbeNo. The model has the following nesting structure: A Pixel is nested within the ProbeNo,the ProbeNo is

Hi, I have a fairly simple linear regression using the lm function. There are about 100 variables and 30,000 rows of data. It runs fine and produces a decent looking R2 value. I'm interested in performing a stepwise variable selection to see if things can be cleaned up a bit. Calling the step function returns ONE iteration (all the variables) and then stops. No errors are reported.