similar to: R2HTML Report number format, or Better Way?

Hi folks! I run the following code to get a CI for a Poisson with lambda=12.73 library(MASS) set.seed(125) x <- rpois(100,12.73) lambda_hat<-fitdistr(x, dpois, list(lambda=12))$estimate #Confidence Intervals - Normal Approx. alpha<-c(.05,.025,.01) for(n in 1:length(alpha)) { LowerCI<-mean(x)-(qnorm(1-alpha[n]/2, mean = 0, sd = 1)*sqrt(var(x)/length(x)))

Hi, R 1.0.1, on Linux(mandrake/RedHat). I am trying to write my first function using R and I need help figuring out the error I have indicated in the Subject line above. The purpose of the function is not to "wow" anyone, but just to serve as a stepping stone so that I might write more complicated functions in the future. First I created my function named "CIfunc" and saved

Another question about lattice: Is there a way to use plotmath in the labels and strips? E.g. xyplot(y~x|group,data=test.df, panel=function(x,y,subscripts,df) { llines(x,y,col="black",lwd=2) llines(x,df[subscripts,"lowerCI"],lty=2,col="#aaaaaa") llines(x,df[subscripts,"upperCI"],lty=2,col="#aaaaaa") },

Forwarded Message: > To: Steve Arthur <sarthur at crick.protogene.com> > From: Thomas Lumley <thomas at biostat.washington.edu> > Subject: Re: [R] couldn't find function "..." > Date: Wed, 5 Jul 2000 16:16:25 -0700 (PDT) > ----- > On Wed, 5 Jul 2000, Steve Arthur wrote: > > > Hi, > > > > R 1.0.1, on Linux(mandrake/RedHat).

R, I want to get means and confidence limits on the original scale for the treatment effect after running a mixed model. The data are: response<-c(16,4,5,8,41,45,10,15,11,3,1,64,41,23,18,16,10,22,2,3)

Hello, I try to set up namespaces for packages. It is fine for several of them, except one whose compilation fails (under Windows XP & R 2.0.0): ---------- Making package svViews ------------ adding build stamp to DESCRIPTION installing NAMESPACE file and metadata Error in parse(file, n, text, prompt) : syntax error on line 21 Execution halted make[2]: *** [nmspace] Error 1 make[1]: ***

Dear all, I know, you get what you pay for. I bought an IP SIP Phone/2.0.6 from safe.com (?55) and the basic functionality is fine. The problem is when it tries to re-register it hangs for a minute or so and you can not dial nor receive any calls. It also has a registration button which causes the phone to do the same once pressed. This however this does not occur when the phone registers

Hi, my data consists of 2 columns: one with the 'year' when daily observation was recorded, the other one consists these observations 'obs', like the following: year obs [3014,] 86 26.01 [3015,] 86 25.66 [3016,] 86 23.92 [3017,] 86 23.84 . . [3018,] 96 22.65 [3019,] 96 23.22 [3020,] 96 23.36 . . [3021,] 97 24.55 [3022,] 97 27.63 [3023,] 97 27.92 [3024,] 97

I am calculating the mean of each column grouped by the variable 'id'. I do this using aggregate, data.table, and plyr. My aggregate results do not match the other two, and I am trying to figure out what is incorrect with my syntax. Any suggestions? Thanks. Here is the data. myData <- structure(list(var1 = c(31.59, 32.21, 31.78, 31.34, 31.61, 31.61, 30.59, 30.84, 30.98, 30.79, 30.79,

Given a data frame consisting of a pointID and 12 pairs of (lat, long) variables, with names latA, longA, latB, longB, ... latL, longL, I want to reshape it into a data frame with the structure point source lat long 1 A ... ... 1 B ... ... I've looked at reshape and plyr, but can't figure out how to do this. Details of my data frame are below

I'm using R on Windows v2.0.1 with the nlme package (v3.1-53) and am finding some unexpected discrepancies in the output of intervals.lme and coef.lme. I've included a toy dataset at the end, but briefly, the data are longitudinal data from couples in marital therapy. Each spouse's relationship satisfaction is measured 4 times; I've fit both linear and quadratic models to the

hello, i'd appreciate help with my glmer. i have a dependent which is an index (MH.index) ranging from 0-1. this index can also be considered as a propability. as i have a fixed factor (stage) and a nested random factor (site) i tried to model with glmer. i read that it's possible to use a quasibinomial distribution, for this kind of data, which i than actually did - but firstly (1)

Hi, I've built a linear model using multiple linear regression which leads me a R-squared value of 73.58%. After that, I used this model to predicted some values based on the test data. Now I'm wondering how: 1. can I measure de R-squared value between the predicted(by the model) and real (observed) values.? 2. Measure the RMSE error . Example: suppose my data its below: REAL

Hi, Try either: res1 <- apply(mydata[,1:2],2,mean) ?res2 <- colMeans(mydata[,1:2]) ?identical(res1,res2) #[1] TRUE # Also if you need to find means for each group ("Ungrazed vs. "Grazed") by(mydata[,-3],mydata[,3],colMeans) #or if column names are "V1", "V2", "V3" aggregate(.~V3,mydata,mean) #or library(plyr)

Hello, I'm with a conceptual doubt regarding Rsquared of both lm() and postResample(library caret). I've got a multiple regression linear model (lets say mlr) with anR² value of 67.52%. Then I use this model pro make predictions with predict() function using the same data as input , that is, use the generated model to predict the value associated with data that I used as input. Next, if

Hello folks, TL;DR: This is my proposed hashing interface based on a proposed standard hashing interface. It also is implemented with a much faster and higher quality algorithm than the current one. This is an *early draft* of the code, looking for initial feedback. There has been recent interest in improving the quality and consistency of LLVM's approach to hashing. In particular, getting

hi Michael, am sorry for the incomplete reply . csv file data havinmg like this , >getSymbols("IBM") >weekly_data = to.weekly(week_name) >dataframe=data.frame(weekly_data) >outputfile_name="F:\\R-programs\\Outputfile.csv" >write.table(dataframe, file =outputfile_name,sep = ",",col.names =TRUE,row.names = T) > datafrom_table <-

On Fri, Sep 14, 2007 at 11:42:18PM -0700, Tanya Lattner wrote: > The 2.1 pre-release (version 1) is available for testing: > http://llvm.org/prereleases/2.1/version1/ > > [...] > > 2) Download llvm-2.1, llvm-test-2.1, and the llvm-gcc4.0 source. > Compile everything. Run "make check" and the full llvm-test suite > (make TEST=nightly report). > > Send

rucker222 wrote: > The drop down layer selection menu at the top left of the screen directly above where the drawing 1 tab is opens upwards off of the screen once the drawing has a few layers on it. jjmckenzie wrote: > Log file please. I loaded a drawing with plenty of layers and then clicked on the layer drop down menu a couple of times before exiting ProgeCAD. Log file below. (sorry

I have a two part question one about statistical theory and the other about implementations in R. Thank you for all help in advance. (1) Am I correct in understanding that Heteroscedasticity is a problem for Generalized Additive Models as it is for standard linear models? I am asking particularly about the GAMs as implemented in the mgcv package. Based upon my online search it seems that some