similar to: Lattice axis list (when relation = "free")

Dear R users: I just got confused some R code used in linear mixed model~ example,two factors,A, B,C,A is fixed ,B,C are random,and B is nested in C,if I wannt to use linear mixed model,are the following code correct for each case? case1:want to know random effect of B, case1<-lme(y~A*B*C,random=~B|C) where "B|C" stand for what?,mean B is nested in C? case2: how to wirte

Good morning, I am analyzing a dataset composed by 364 subjects and 13 binary variables (0,1 = absence,presence). I am testing possible association (co-presence) of my variables. To do this, I was trying with cluster analysis. My main interest is to check for the significance of the obtained clusters. First, I tried with the pvclust() function, by using method.hclust="ward" and

I have a function "eval.delta" which does what I want but isn't very elegant. I have consulted the R documents, MASS, and S Programming. Is there a practical way to optimize the code? Thank you very much. Peter B. Function: eval.delta <- function(delta){ cat("VALUES\n") vlr <- NULL k <- 0 for(j in 1:length(delta)) if(delta[j] <= 2){

Dear R people, I have to deal with the output of a function which comes as a matrix of vectors. You can reproduce the structure as given below: x <- list(c(1,2,4),c(1,3,5),c(0,1,0), c(1,3,6,5),c(3,4,4,4),c(0,1,0,1), c(3,7),c(1,2),c(0,1)) data <- matrix(x,byrow=TRUE,nrow=3) colnames(data) <- c("First", "Length", "Value") rownames(data)

Hello, Everyone. I have a question about llvm's "Combine redundant instructions(instcombine)" pass. I have tested instcombine pass by writing the following three test cases. But, CASE3 is not optimized as I expected. Is this behavior expected? The version of llvm is: clang version 5.0.1 (tags/RELEASE_501/final 325232) Option of clang command is: clang -O1 a.c -S -emit-llvm

From: Suravee Suthikulpanit <suravee.suthikulpanit@amd.com> This patch add an additional logic to check for the often case when the special->handle is not initialized due to firmware bugs. but the special->usedid is correct. If users overide this using the command line option ivrs_ioapic, then it should use the value instead. --- This patch is supposed to follow the patches:

Hello, I've some problem with the ggplot2. Here's a small example: --8<-- library(ggplot2) molten <- data.frame(date=c('01','01','01','01', '02','02','02','02'), channel=c('red','red','blue','blue',

Greetings All. First let me introduce my situation Machine1: Pdc Samba + OpenLDAP(master) Machine2: Bdc Samba + OpenLDAP(slave) LDAP stores Samba and POSIX information for each user. Case1: I login to Machine1 and invoke smbpasswd. I change my passwords (samba and posix without any problem). In next few seconds they get propagated to Machin2 wher I can login with new credentials. ldap log

Hello, I have a couple questions about removing rows from a data frame and creating a new data frame with the removed values. I provided an example data frame (d) below. Questions: 1) How can I search for "-999.000" and remove the entire row from data frame "d"? (all -999 values will be in sd_diff) 2) Can I create a new data frame "d.new" that only contains the

Dear all, I have a big data matrix and I want to convert those data into weekly basis which means 7 days needs to be avaraged and aggregate a single value > dput(test) structure(list(locid = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,

Hi list, I am trying to calculate the sensitivity, specificity, and odds ratio(and confidence interval). Say, my data looks like this 42.53, 37.56, 40.51, 32.67, 38.19, 81.74, 41.55, 68.94, 59, 63, 54.13, 48.85, 50.46, 51.78 Is there any packages in R that does this? Espeically the odds ratio confidence interval. Mike [[alternative HTML version deleted]]

Hi, i need to draw a plot with means of values, reading a table from datafile. Example of datafile: Days Weight 0 178.00 0 250.00 0 242.00 0 239.00 0 223.00 0 188.00 0 237.00 0 212.00 0 273.00 0 191.00 0 173.00 0 233.00 0 227.00 0 253.00 0 232.00 4 177.00 4 249.00 4 241.00 4 238.00 4 222.00 4 188.00 4 236.00 4 211.00 4 272.00 4 190.00 4 172.00 4 232.00 4 226.00 4 252.00 4 231.00 if i use

Hi list, I'm sure the explanation must be laughably simple to the experts out there, but I just could figure it out. I have a simple data frame that looks like, >head(da.off) DDate OffP 1 2005-01-01 41.23 2 2005-01-02 44.86 3 2005-01-03 44.86 4 2005-01-04 43.01 5 2005-01-05 45.47 6 2005-01-06 48.62 where the first column DDate currently is character, and OffP is numeric. I want

I have some data which I would like to display with dotchart. The labels are very long, so the chart becomes too small. Setting cex=0.7 seems to be a good compromise, but the gap between the text and the chart still is too large. I did not find a "gap" parameter in the description of dotchart... Thanks for any help. D. Trenkler "a" <- structure(c(103.35, 36.73, 55.09,

R I get a daily feed of data over the internet that I keep in various .csv files. I have built a function that reads that data into R for me: getMarketData<-function(market) { library(zoo) pathname<- "C:/DATA/" files<-c("AN_REV.csv","AX_REV.csv","BN_REV.csv") markets<-c("AUS","DAX","GBP")

When I try to convert the zoo object to a timeSeries object, which would allow me to utilize Rmetrics packages, I get an error message. > Data<-read.zoo("c:\\DOWUBSPRICING.txt,na.strings="NA",sep="\t",header=T) > is(Data) "zoo" > as.timeSeries.zoo(Data) Error in .local (.Object, . ) Is this happening because I am using daily data?

The current llvm/llvm-gcc-4.2 2.6 branch passes all of the Polyhedron 2005 benchmarks built with its gfortran. The results compare as follows... Compile Command : gfortran -ffast-math -funroll-loops -msse3 -O3 %n.f90 -o %n benchmark gcc-4.2.4 llvm-gcc-svn llvm-gcc-2.6 llvm-gcc-2.6 at -m32 20081031 -m32 at -m32 at -m64 ac 18.30

I have the following timeseries "tab" ===================================== > str(tab) mts [1:23, 1:2] 79.5 89.1 84.9 75.7 72.8 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "Ipex...I" "Omel...E" - attr(*, "tsp")= num [1:3] 2006 2008 12 - attr(*, "class")= chr [1:2] "mts" "ts" > tab

On 2016-05-25 19:13, Kelly Lesperance wrote: > Hdparm didn?t get far: > > [root at r1k1 ~] # hdparm -tT /dev/sda > > /dev/sda: > Timing cached reads: Alarm clock > [root at r1k1 ~] # Hi Kelly, Try running 'iostat -xdmc 1'. Look for a single drive that has substantially greater await than ~10msec. If all the drives except one are taking 6-8msec, but one is very

Hi, I have a query on regression output generated by R. > result=lm( Y~X , data=trail) > summary(result) After running this 2 statements the following output is generated. Call: lm(formula = Y ~ X, data = trail) Residuals: Min 1Q Median 3Q Max -245.30 -90.77 -30.30 54.99 532.78 Coefficients: Estimate Std. Error t value Pr(>|t|)