similar to: R help

Folks, Is there a parameter somewhere in RODBC that enables more columns to be retrieved from an Excel worksheet? # This next bit uses an undocumented call in RODBC z <- odbcConnectExcel("./BBaselinePtQaires_apr2011.xls") BQ <- sqlFetch(z, "BBaselinePtQaires") Gives me: z RODBC[1] And BQ 134 obs. of 59 variables I have all the rows in the worksheet but only the

Hi all I have a set of data whose scatter plot shows a very nice power relationship. My problem is when I fit a Power Trend Line in an Excel spreadsheet, I get the model y= 44.23x^2.06 with an R square value of 0.72. Now, if I input the same data into R and use model< -nls(y~ a*x^b , trace=TRUE, data= my_data, start = c(a=40, b=2)) I get a solution with a = 246.29 and b = 1.51. I have tried

I'm running R 2.15.2 on Max OS X 10.6.8 If I write a simple file Data1<-1 DF<-data.frame(Data1) colnames(DF)<-"Col1" and write to a csv file write.table(DF,file="Data.csv",sep=",",row.names=FALSE,col.names=TRUE) I can then append to it no problem Data2<-2 Data3<-4 DF2<-data.frame(Data2) DF3<-data.frame(Data3)

Are they the same with .RData being the newer format?? Thanks, ...Tao

Hi, I'm trying to user lmer function from lmerTest package because, if I understood correectly, it allows to make better inference than lmer method from lme4 package. However, whatever I do I keep getting this error: Error in lme4::lFormula(formula = mark ~ ssCount + sTime+ : rank of X = 1660 < ncol(X) = 1895 any ideas what could be a problem? thanks, Srecko [[alternative HTML

Dear all, I have an R script that uses Rcpp, and I have been trying to parallelize it using mclapply (I tried with the multicore and the parallel library) Sometimes (not always, interestingly), the CPU use for each core drops, usually so that the total over all cores reaches 100%, i.e., as fast as if using just one single core fully. I tried my code directly from within emacs, and also using a

Hello r-help, I've been banging my head against the computer in an attempt to learn how to divide my matrix into segments by rows. I want to be able to return each segment as a newly named object. I've tried looking at the apply functions and creating a for loop but brain no work. Here's the basic starting objects that I believe would be needed to separate the matrix. mat <-

Dear R users, I am running simulations (1000), and in my simulation I am looking at specific sums. For example, if the sum is >=4 then count this, if say <3, then don't count, if the sum=3, then generate a random number from uniform distribution, if this number is say less than 0.5, then count this sum, if greater than 0.5, then don't count. I am having trouble with introducing this

Hi all: My OS is 32bit winxp,but I wanna install 64bit R2.14.1. >From the following website,it says "You can also go back and add 64-bit components to a 32-bit install, or vice versa" http://cran.r-project.org/bin/windows/rw-FAQ.html#Can-both-32_002d-and-64_002dbit-R-be-installed-on-the-same-machine_003f Does it mean that I can install and run 64bit R2.14.1 under 32bit

In the following data.frame there are 6 columns, but 7 are written to the CSV file. install.packages("pmlr") library(pmlr) data(enzymes) write.table(enzymes, sep=",", eol="\n",file="albert.csv")

Hi, I am trying to normalize some data. First I fitted a principal curve (using the LCPM package), but now I would like to apply a transformation so that the curve becomes a "straight diagonal line" on the plot. The data used to fit the curve would then be normalized by applying the same transformation to it. A simple solution could be to apply translations only (e.g., as done after a

Hello R, could you tell me please, how to fix this issue? There is installed RStudio-2.15.2 and the next steps where follow but the message appears: http://cran.r-project.org/web/packages/RMySQL/INSTALL): > > 1. Download the RMySQL_0.9.tar.gz file to the folder C:\Program > Files\R\R-2.15.1\bin\x64 > 2. Open a Windows command line, and change directory to that folder > 3.

Hello, i am working in origin pro, i want to plot a graph as like a pdf attached but with black and white lines. here radial axis varies from 0 to 1. and angular axis from 0 degree to 60 degree.and third axis which is depend on both radial and axial gives non intersecting lines. how can i read the data from plot for replot. vikas -------------- next part -------------- A non-text attachment was

I have two regressions to perform - one with a metric DV (-3 to 3), the other with an ordered DV (0,1,2,3). Neither normal distribution not homoscedasticity is given. I have a two questions: (1) Some sources say robust regression take care of both lack of normal distribution and heteroscedasticity, while others say only of normal distribution. What is true? (2) Are there ways of using robust

is it possible to throw a stop() that is so hard that it will escape even tryCatch? /iaw ---- Ivo Welch (ivo.welch at gmail.com)

Dear all, In a plot command like xyplot(Y~X|ID*PERIOD,data=...) xyplot will generate all the possible ID*PERIOD combinations. But not all of them have data in there. So I have a lot of empty plots. How can I suppress those empty plots and ask xyplot only to generate plots actually with data. Thanks. Jun [[alternative HTML version deleted]]

Dear expert How can we plot diagonal across (from bottom-left-hand corner to top right-hand corner), at any given coordinate range For example > plot(c(-2,3), c(-1,5), type = "n", xlab="x", ylab="y", asp = 1) or > plot(c(0,1000), c(0,334), type = "n", xlab="x", ylab="y", asp = 1) I tried abline with the following but failed:

How to call a function from another r file ? Anyone can help me . Having a function named like fun1 which is saved in r file file1.r and i have another r file like file2.r, and i need to call the fun1 (which is in file1) within file2. Thank you -- View this message in context: http://r.789695.n4.nabble.com/function-call-from-another-r-file-tp4650627.html Sent from the R help mailing list

Dear All   I have the following data (somewhat simplyfied):   TINF <-1 a <-c(500,750,1000,1250,1500,1750,2000) b <-c(8,12,18,24,36,48,60,72,96)   following function:   infcprodessa <-function (D, tin, tau, ts)   (D * (1 - exp(-0.048 * tin))/(tin * (0.048*79) * (1 - exp(-0.048 * tau)))) * exp(-0.048 * (ts - tin)) z <-sapply(1:1, function(n) infcprodessa(1000,TINF,12,12-TINF))   is

Jeff, I wanted to let you know that your function is faster than generating the directional circular permutations and weeding. Here is the time for n = 10. I compared with just doing the permutations, there is no point in proceeding further with the weeding since it is slower at the start itself. system.time(directionless_circular_permutations(10)) user system elapsed 1.576 0.000