similar to: Book recommendation for newbie to stats and R?

In Henric's recent post, he included this output: @BOOK{R:Harrell:2001, AUTHOR = {Frank E. Harrell}, TITLE = {Regression Modeling Strategies, with Applications to Linear Models, Survival Analysis and Logistic Regression}, PUBLISHER = {Springer}, YEAR = 2001, NOTE = {ISBN 0-387-95232-2}, URL =

I hope this question is sufficiently different from the other requests for book recommendations that it's not repetitious. If not, I apologize in advance. I'm curious what standard reference books working statisticians, or biostatisticians, have within easy reach of their desk. I'm a computer systems administrator, and have a two-foot bookshelf directory under my monitor that contains

I'm looking for a book for someone completely ignorant of statistics who wishes to learn both statistics and R. I've found three possibilities, one by Verzani ("Using R for Introductory Statistics"), one by Crawley ("Statistics: An Introduction using R"), and one by Dalgaard ("Introductory Statistics with R"). Do these books have different emphases,

I've been working with R for all of about 8 hours, so anyone with more experience than this should be able to help me. General comments about my methods of work are also welcomed. I have a table that I've imported thusly: > w <- read.table("woodford.data", header=T) > w start therms gas KWHs elect temp days 1 10-Jun-98 9 16.84 613 63.80 75 40 2

I think I've gotten my Emacs/Sweave/R system set up correctly, thanks to Vincent and Jim, but I haven't been successful getting my first document produced. I'm trying to use one of Friedrich Leisch's examples, http://www.ci.tuwien.ac.at/~leisch/Sweave/example-1.Snw. I cut and pasted the text into a document sweaveexample.Rnw in Emacs. It seemed to be processed successfully with R:

http://bugzilla.mindrot.org/show_bug.cgi?id=335 dyw at iohk.com changed: What |Removed |Added ---------------------------------------------------------------------------- Severity|major |normal Keywords| |help-wanted OS/Version|Linux |BSDI

We just studied randomized block design analysis in my statistics class, and I'm trying to learn how to do them in R. I'm trying to duplicate a case study example from my textbook [1]: > # Case Study 13.2.1, page 778 > cd <- c(8, 11, 9, 16, 24) > dp <- c(2, 1, 12, 11, 19) > lm <- c(-2, 0, 6, 2, 11) > table <- data.frame(Block=LETTERS[1:5], "Score

I am new to using R and would appreciate some advice on which books to start with to get up to speed on using R. My Background: 1-C# programmer. 2-Programmed directly using IMSL (Now Visual Numerics). 3- Used in past SPSS and Statistica. I put together a list but would like to pick the "best of" and avoid redundancy. Any suggestions on these books would be helpful (i.e. too much

I'm trying to get R to simulate the sum of the values on 10 fair dice (yes, it's related to a homework problem, but is not the problem itself). I tried to do this: > rep(sum(sample(1:6,100,replace=T)), times=10) [1] 341 341 341 341 341 341 341 341 341 341 and noticed that sum(sample()) seems to be only evaluated once. How can I overcome this, so that I get a vector of values that

I have a very large dataframe and wish to extract a subset of rows. I have a two column matrix listing the starting and ending indices of one subset on each row. My idea is to create a vector of indices that could be applied to the dataframe and I have a solution using a for loop (below). But surely there is some more elegant way to do this! I looked thorough the archives without

For several years, I have been using Splus to analyze an ongoing series of datasets that have a bimodal distribution. I have used the following functions, in particular the ms() function, to estimate the parameters: two means, two standard deviations, and one proportion. Here is the code I've been using in S: btmp.bi <- function(vec, p, m1, m2, sd1, sd2) {

I'm trying to replicate some of the examples from my textbook in R (my text uses Minitab). In this problem, I'm trying to construct a 95% confidence interval for these distance measurements [1]: > # Case Study 7.4.1, p. 483 > x <- scan() 1: 62 52 68 23 34 45 27 42 83 56 40 12: Read 11 items > alpha<-.95 > mean(x) + qt(c((1-alpha)/2, 1-((1-alpha)/2)), df=length(x)-1) *

I'm trying to get R, Sweave, ESS and XEmacs or emacs all installed and working together on my Windows XP Pro system. I've got R 2.6.0 working just fine, installed from the R Windows installer. I also have CYGWIN_NT-5.1 with XEmacs 21.4 working okay. Can anyone point me to any documentation on how to bring these together so that R code typed in Xemacs can be run in R? I found the ESS

Is this how a t hypothesis test is done when I don't have the actual data, but just the summarized statistics: > #Homework 9.2.6 [1] > n<-31 > xbar<-3.10 > s_x<-1.469 > m<-57 > ybar<-2.43 > s_y<-1.35 > s_pooled<- (((n-1)*s_x^2) + ((m-1)*s_y^2)) / (n + m - 2) > s_pooled [1] 1.939521 > t_obs <- (xbar - ybar) / (s_pooled * (sqrt(1/n + 1/m)))

Does anyone have an idea of how one might plot male and female symbols on a graph using R? Thanks! .................................................................. George W. Gilchrist Email #1: gwgilc at wm.edu Department of Biology, Box 8795 Email #2: kitesci at cox.net College of William & Mary Phone: (757) 221-7751 Williamsburg, VA

I'm looking for a function in R similar to t.test() which was generously pointed out to me yesterday, but which can be used for normally distributed data. To recap yesterday: > x <- scan() 1: 62 52 68 23 34 45 27 42 83 56 40 12: Read 11 items > alpha<- .05 > t.test(x) One Sample t-test data: x t = 8.8696, df = 10, p-value = 4.717e-06 alternative hypothesis: true

There must be a better way to select the rows after 22-Apr-2004 and before 01-Sep-2004 with a temperature below 65 than this: > before2sw1 <- subset(energy.data, as.Date(start, format="%d-%b-%y") < as.Date("01-Sep-04", format = "%d-%b-%y")) > before2sw2 <- subset(before2sw1, as.Date(start, format="%d-%b-%y") >=

In S-Plus, there is a function ms() [minimum sums] that estimates parameters in a multivariate model and returns, along with the estimates, a loglikelihood score. It's very handy, but I have not found an R version yet. Does anyone know if such a thing exists? Thanks. Cheers, George ================================================================== George W. Gilchrist

I need to extract the degrees of freedom and log likelihoods from a series of mixed models computed using lmer/lme4. If I ask for logLik (lmer.object), I get something like > logLik(lmer.object) 'log Lik.' -177.1000 (df=10) Can I easily get that df from there (or elsewhere) into an object? Thank you for any ideas. George

[If I knew who to report this to privately, I would. Sorry to embarrass anyone who's just trying to contribute to the R-project.] There seems to be some oddities with the RSiteSearch web page. When I enter 'RSiteSearch("console")' I'm taken to http://search.r-project.org/cgi-bin/namazu.cgi?query=console&max=20&resu