similar to: strange behavior, adds new field by non-existent field

I have a number of space separated files of weather data, with some equivalent column names, and differing number of fields in each file. Some of the files have 40 or more vars, but I only want a subset of the fields. I can use colClasses with read.table to drop some of the fields, but only if I know where those columns are in the first place, and they're not always in the same place. So I

It looks like a timezone issue, and it's causing confusion to me at least. My original data: gmt <- c("19880101 0000", "19880101 0100", "19880101 0300", "19880101 0400", "19880101 0500", "19880101 0600") These were converted to local dates/times with akst<-strptime(gmt,format="%Y%m%d %H%M")-(3600*9) # because I want

Dear all I am trying to fit Variable Coefficients Models on Unbalanced Panel Data. I managed to fit such models on balanced panel data (the example from the "plm" vignette), but I failed to do so on my real, unbalanced panel data. I can reproduce the error on a modified example from the vignette: > require(plm) > data("Hedonic") > Hed <- pvcm(mv ~ crim + zn + indus

Hi folks, I am confused whether the following is a bug or it is fine Here is the explanation a <- zoo(c(NA,1:9),1:10) Now If I do rollapply(a,FUN=mean,width=3,align="right") I get > rollapply(a,FUN=mean,width=3,align="right") 3 4 5 6 7 8 9 10 NA NA NA NA NA NA NA NA But I shouldn't be getting NA right ? i.e for index 10 I should get (1/3)*(9+8+7)

Hi Ya'll I'm trying to install the zoo library... I've downloaded about 5 or 6 of their releases (inc. the latest one), all of them giving me the same syntax error when trying to install... Anyone seen this problem before? its not the "lib" argument that is the problem (ive been installing other packages using this exact format with no problem... just zoo is the problem.

Dear all I am working on unbalanced panel data and I can readily fit a "pooling" model using plm(), but not a "within" or "random" model. Reproducing the examples in vignette("plm") and in the AER package I encountered no such issues. ##unfortunately I cannot disclose the data, and it is too big anyway > dim(ibes.kld.exp.p[x.subs , ]) [1] 13189 34

I am trying to read an xlsx spreadsheet (1506 rows, 501columns) all populated but getting the following error: Please advise as to how to get around this issue. > res <- read.xlsx("c:\\BSE_v2.xlsx",1) Error in .jcall("RJavaTools", "Ljava/lang/Object;", "invokeMethod", cl, : java.lang.OutOfMemoryError: Java heap space Here is the session info:

Hi together, below is a small example which produces outcome I do not understand, namely that the median function works fine on a data.frame without negative numbers, but doesn't work on a data.frame with one negative number. I'm sure there is a reasonable explanation for that or better, that I'm doing something wrong and someone could guide me how to solve it. I tried googling it,

Dear all, I was intrigued by the ctree command and wanted to check it out. I first ran the demo with example(ctree) and did get the survival graphs in the end. Upon doing this with my own data and yielding a "Invalid operation on a survival time" I tried to rerun example(ctree) and now I also get "Invalid operation on a survival time" after the example runs plot(GBSG2ct)...

This is the first time that I have tried to update packages with a tinkered around with .Rprofile. I start R with R --vanilla and it does not load my .Rprofile, but when I issue the command update.packages() R downloads the packages as expected, but then seems to load .Rprofile before compiling the packages sources. What am I doing wrong? kindest regards, Stephen Sefick see- Session info

The LegalizeDAG.cpp file has this code in SelectionDAGLegalize::PromoteNode: case ISD::BSWAP: { unsigned DiffBits = NVT.getSizeInBits() - OVT.getSizeInBits(); Tmp1 = DAG.getNode(ISD::ZERO_EXTEND, dl, NVT, Tmp1); Tmp1 = DAG.getNode(ISD::BSWAP, dl, NVT, Tmp1); Tmp1 = DAG.getNode(ISD::SRL, dl, NVT, Tmp1, DAG.getConstant(DiffBits, TLI.getShiftAmountTy()));

Hi, I haven't tried the code yet. Is there a way to parse this data using R and create bar plots so that each program's 'RAM used' figures are grouped together. So 'uuidd' bars will be together. The data will have about 50 sets. So if there are 100 processes each will have about 50 bars. What is the recommended way to graph these big barplots ? I am looking

Eli, Using the variables from the original IR, assuming tmp == tmp1 and assume the value is not nan ogt(tmp, tmp1) is !isnan(tmp) && !isnan(tmp1) && tmp > tmp1, or false ule(tmp, tmp1) is isnan(tmp) || isnan(tmp1) || tmp <= tmp1, or true So, this is invalid, or am I misunderstanding what ogt and ule stand for? Assuming this is valid, why convert comparison instructions

On Wed, May 20, 2009 at 4:55 PM, Dan Gohman <gohman at apple.com> wrote: > Can you explain why you chose the approach of using a new pass? > I pictured removing LegalizeDAG's type legalization code would > mostly consist of finding all the places that use TLI.getTypeAction > and just deleting code for handling its Expand and Promote. Are you > anticipating something more

On May 20, 2009, at 1:34 PM, Eli Friedman wrote: > On Wed, May 20, 2009 at 1:19 PM, Eli Friedman > <eli.friedman at gmail.com> wrote: > >> Per subject, this patch adding an additional pass to handle vector >> >> operations; the idea is that this allows removing the code from >> >> LegalizeDAG that handles illegal types, which should be a significant

Some of the optimizations that the first DAG combine performs is counter productive for our 8-bit target. For example in: // I dropped the types because they are irrelevant. // Excuse me for changing the syntax... store %tmp1, %var %tmp2 = load %var %tmp4 = add %tmp3, %tmp2 Since load is the only user of var and since var has just be stored to, it assumes that %tmp1 is alive and it goes ahead

Hello! I am merging two datasets and I have encountered a problem with sort. Can someone please point me to my error. Here is the example. ## I have dataframes, first one with factor and second one with factor ## and integer > tmp1 <- data.frame(col1 = factor(c("A", "A", "C", "C", "0", "0"))) > tmp2 <- data.frame(col1 =

Dear Daniel, Thank you for your email. According to your suggestion, I tried to use the shared memory filesystem for data exchange between the host machine and the container. The steps are as follows: 1) create an empty file in the host machine (/tmp1/file1). 2) run #chmod 777 /tmp1 and #chmod 777 /tmp1/file1. 3) expose /tmp1 to the container by configuring the container with the following XML

Dear R users, I have a simple problem I cannot solve, but I sure you can help. I have two vector, let say > tmp1 <- c("a", "a", "b", "c") > tmp2 <- c("a", "a", "b", "c", "c", "d") and I want to create a matrix of two column for which I have all the combinations of the same character,

Suppose I have a data frame, such as the one below: tmp <- data.frame(index = gl(2,20), foo = rnorm(40)) And further assume it is sorted by index and then by the variable foo. tmp <- tmp[order(tmp$index, tmp$foo) , ] Now, I want to grab the first N rows of tmp for each index. In the end, what I want is the data frame 'result' tmp1 <- subset(tmp, index == 1) tmp2 <-