similar to: Data frame self-join with no duplicates

Hi all, I was trying to fit a Gamma hierarchical model using "glmer", but got weird error message that I could not understand. On the other hand, a similar call to the glmmPQL leads to results that are close to what I expect. I also tried to change tha "nAGQ" argument in "glmer", but it did not solve the problem. The model I was fitting has a simple structure - one

Xend will do a hypercall to destory domain when creating VTI guest fail. If "is_vti" not be set at this point, HV will call relinquish_vcpu_resource() which belong to domU. It may try to free a NULL pointer, so dom0 crash. This patch fix it. Signed-off-by, Zhang Xin < xing.z.zhang@intel.com > Good good study,day day up ! ^_^ -Wing(zhang xin) OTC,Intel Corporation

Dear R users, I have two data frames that were read from text files as follows: x_data <- read.table("x.txt", header = TRUE, sep = "|", quote = "\"'", dec = ".",as.is = TRUE,na.strings = "NA",colClasses = NA, nrows = 3864284, skip = 0, check.names = TRUE,fill=TRUE, strip.white = TRUE,

Dear R helpers,     Yesterday I had raised following query which was addressed by Mr Ellison. The query and the wonderful solution as provided by Mr. Ellison are as given below.    ## PROBLEM   I am calculating the 'Yield to Maturity' for the Bond with following characteristics.    Its a $1000 face value, 3 year bond with 10% annual coupon and is priced at 101. The yield to maturity can be

Hi Dennis, Thanks for your quick response and sorry for not being clear. That helped, but I need an actual matrix of e.g., 12 x 12 and those functions give me a matrix with only the "filled" locations. I need a 12 by 12 matrix with sums (0 if there's not data and the actual sum where there is) as follows: 1 2 3 4 5 6 7 8 9 10 11 12 1 0 0 0 . . . . . . 0 0 0 2 0 0 0 . 3 0

I found this paper on ANOVA on unequal error variance. Has this be incorporated to any R package? Is there any textbook that discuss the problem of ANOVA on unequal error variance in general? http://www.jstor.org/stable/2532947?cookieSet=1

HI. I make this code: getdata<-function('a','b','c' ,'d','e','f'){ drv <- dbDriver("SQLite") con<-dbConnect(drv, "sqlite.db") lt<-dbListTables(con) myf<-data.frame(NULL) for (i in 1:length(lt)) { myfile<-dbReadTable(con,lt[i]) myfile1<-myfile[-c(14:44)] myfile1$MODEL<-gsub(" ",

Dear R users, I need to merge two data frames based on both equal and unequal comparisons. The "sqldf" package used to work well , but today, I cannot resolve the following error by reinstallation of the sqldf package. Can anyone suggest a different way to perform this kind of merge function? Thank you, Ding > DMRlog2pbde47DMS <- sqldf("select * from DMR_log2pbde47 as a

Dear subscribers: I am using the following code to read a large number of big text files: library(sqldf) tempd <- file(XXXX) tempdx <- sqldf("select * from tempd", dbname = tempfile(), file.format = list(header = T, sep="\t", row.names = F)) The problem is: all my numberical variable become factor (maybe because these columns all contain missing value). It would be

Hi list, Can anyone tell my why the following does not work? Thanks a lot! Your help is very much appreciated. DF = data.frame(read.table(textConnection(" B C D E F G 8025 1995 0 4 1 2 8025 1997 1 1 3 4 8026 1995 0 7 0 0 8026 1996 1 2 3 0 8026 1997 1 2 3 1 8026 1998 6 0 0 4 8026 1999 3 7 0 3 8027 1997 1 2 3 9 8027 1998 1 2 3 1 8027 1999

Dear Group, Is there a more efficient way to create a data frame structure (using rep I guess?) require(plyr) week <- rdply(10, data.frame(week = 1:52)) names(week) <- c("Year", "Week") week$Year <- week$Year + 2000 Basically trying to create a year and week data frame to start appending data to for a ggplot. Many thanks. [[alternative HTML version deleted]]

Hi , I would like to use ggplot2 to plot a matrix as an image. You can copy paste the following Data<-matrix(data=rnorm(900,80,20),nrow=30,ncol=30) lengthOut<-5 Lengths<- 15 library(reshape2) library(ggplot2) tdm <- melt(Data) ggplot(tdm, aes(x = Var2, y = Var1, fill = factor(value)),levels=seq(0,1,by=0.1)) +                   labs(x = "MHz", y =

I have a very large tab-delimited file, too big to store in memory via readLines() or read.delim(). Turns out I only need a few hundred of those lines to be read in. If it were not so large, I could read the entire file in and "grep" the lines I need. For such a large file; many calls to read.delim() with incrementing "skip" and "nrows" parameters, followed by grep()

Hi group, I imported 16 data frames using the function "list.files" temp <- list.files(path="...........") myfiles = lapply(temp, read.table,sep = "") Now I have 16 data set imported in R window. I want to combine them by row and tried some thing like (Here I am considering only 20 columns) for(i in 1:16){ data<- cbind(myfiles[[i]][,1:20]) } but it

I am a SAS user currently evaluating R as a possible addition or even replacement for SAS. The difficulty I have come across straight away is R's apparent difficulty in handling relatively large data files. Whilst I would not expect it to handle datasets with millions of records, I still really need to be able to work with dataset with 100,000+ records and 100+ variables. Yet, when reading

Dear All, Is sqldf equipped with delete queries? I have tried delete queries but with no success. Thanks in advance, Paul

Hello, Everyone. Does anyone know how to create a Nightingale’s Rose chart by using R? Hopefully, the graph could be displayed like this: http://mbostock.github.com/protovis/ex/crimea-rose.html Thanks a lot. Kind regards, Henry [[alternative HTML version deleted]]

I have a (very big - 1.5 rows) dataframe with a (POSIXt" "POSIXlt") column h (hour). Surprisingly, I cannot calculate a simple aggregate over the dataframe. > n.h1 = sqldf("select distinct h, count(*) from x group by h") Error in sqliteExecStatement(con, statement, bind.data) : RS-DBI driver: (error in statement: no such table: x) In addition: Warning message: In

Hi All, I'm conducting a meta-analysis and have taken a data.frame with multiple rows per study (for each effect size) and performed a weighted average of effect size for each study. This results in a reduced # of rows. I am particularly interested in simply reducing the additional variables in the data.frame to the first row of the corresponding id variable. For example:

Hi all, I am attempting to learn SQL through sqldf... One task I am particularly interested in is merging separate (presumably large) files into a single table without loading these files into R as an intermediate step (by loading them into SQLite and merging them there). Taking a step back, I've considered these alternatives: 1) I know if I use straight SQLite commands I might use the