search for: hinkley

I propose the following enhancements and changes to plot.lm(), the most important of which is the addition of a Residuals vs Leverage plot. (1) A residual versus leverage plot has been added, available by specifying which = 5, and not included as one of the default plots. Contours of Cook's distance are included, by default at values of 0.5 and 1.0. The labeled points, if any, are those

...are shown, as for the 'boot' package: ----------------------------------- citation('boot') To cite the 'boot' package in publications use: Angelo Canty and Brian Ripley (2012). boot: Bootstrap R (S-Plus) Functions. R package version 1.3-7. Davison, A. C. & Hinkley, D. V. (1997) Bootstrap Methods and Their Applications. Cambridge University Press, Cambridge. ISBN 0-521-57391-2 ----------------------------------- Is there any way to show the two bib entries for cases similar to the 'boot' package ? sessionInfo() R version 2.15.2 (2012-10-26)...

...; To: s-news at lists.biostat.wustl.edu > Subject: [S] Study group on bootstrap > > > Hi > I am looking for participants for an e-mail based study > group on bootstrap methods based on reading 'Bootstrap > Methods and their Application' by Davison and Hinkley. > > My idea is to form a small group that reads the chapters of > the book for aggreed-on deadlines (with a lot of latitude) > and then help each other with understanding the material. > Everybody sends questions to the group and anybody in the > group answers to...

Dear Lillian, I tried to estimate parameters for time series regression using time series bootstrapping as described on page 434 in Davison & Hinkley (1997) - bootstrap methods and their application. This approach is based on an AR process (ARIMA model) with a regression term (compare also with page 414 in Venable & Ripley (2002) - modern applied statistics with S) I rewrote the code for R (this comes without any warranty): fit <- fu...

Hi, I am new to R (I have most of my experience in SAS and SPSS). I was wondering if anyone has used both Resampling Stats and R, and could comment on strengths/relationships. Also, I have no clue on how to do the various examples from the book "Resampling: The New Statistics" in R. Can anyone give me some possible starting points? Or websites/books? Thanks, Brandon

Good Morning: I posted an initial question a few days ago and I received some good advice from two R experts. I have re-examined the Davison-Hinkley text paying close attention to the examples of the boot() and boot.ci() in that text and the single example of a similar process in the MASS book (not the MASS package manual as I initially misunderstood). I think I understand how the stratified sampling works and how the index plays a role in the...

Does R have a bootstrap command like SPlus, or do we have to form our own code if we want to do bootstrapping in R? Jason Parcon Western Michigan University e-mail addresses: s0parcon at wmich.edu parcon at stat.wmich.edu -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hello, I downloaded R today because I was told it has very good bootstrapping abilities. What I need to do is to program it (or use an existing program) to bootstrapping test for multimodality using nonparametric kernel density estimates as proposed by Efron and Tibshirani (1993). If anyone can get me started, I will be immensely grateful. Thanks. Sangeeta

Dear R Users, I suppose this is a school boy question, but here it is anyway. I'm trying to re-create the residuals for a poisson GLM with simulated data; x<-rpois(1000,5) model<-glm(x~1,poisson) my.resids<-(log(x)- summary(model)$coefficients[1]) plot(my.resids,residuals(model)) This shows that my calculated residuals (my.resids) are not the same as residuals(model). p 65 of

Hi all, Looking to calculate the expected mean and variance of a ratio distribution where the source distributions are gaussian with known parameters and sample values are correlated. I see (from wikipedia: http://en.wikipedia.org/wiki/ Ratio_distribution#Gaussian_ratio_distribution) that this calculation is quite involved, so I'm hoping that someone has already coded a function to

Hola! Tengo que hacer un proyecto acerca del paquete bootstrap de R, alguien podría facilitarme información completa (y en español a ser posible) acerca de este paquete? Muchas gracias de antemano, y un saludo. [[alternative HTML version deleted]]

Does anyone know what algorithm R uses in glm, family=binomial (i.e. a logit model)? I assume that it's in the source somewhere, but I wasn't able to find it. I'd like to know what file it's in (in a unix distribution of R). Thanks for your help. --------------------------- Barnet Wagman wagman at enteract.com 1361 N. Hoyne, 2nd floor Chicago, IL 60622 773-645-8369

....2.2, Windows). In one of these scripts, I've bootstrapped the prediction success rate under the discriminant function (lda). The bootstrap() functions are proprietary to S-Plus and there aren't exact equivalents in R. The closest is Canty's library boot based on the Davidson and Hinkley book. Unfortunately, I haven't been able to map the commands I used in the bootstrap() function of S-Plus to the boot() function in the boot library of R (and also S-Plus). Below is an example of one line from this S-Plus script. The particular element I'm having trouble mapping to bo...

...n gives a 92% correct classification rate. Anyway, my question is this--- WHat is the best or proper way to present the results of a bootsrapped mean and standard deviation? I ask this since looking through both Efron's and Tibshirani's AN INTRODUCTION TO BOOTSTRAP, and Davison's and Hinkley's book they don't necessarily address a question this simple. I don't think the editor is going to one to see 48 histograms (8 variables for 3 groups, mean and standard deviation). Or should I quit looking at boot and bootstrap, and just do the sample with replacement that is in R, an...

Dear R mailing list, Greetings!!! I'm doing a graphical test of suitability for the aircondit data. I actually just followed the exercise in Davison and Hinkley's book of Graphical Test for model checking. The program for testing if it comes from an exponential distribution seems to be running okay but the program for the gamma distribution distribution is running away :-). I hope you can spare sometime to check what I have written below. I am also...

...nd Gong (the TAS "leisure look" paper), or the Efron & Tibshirani 1993 bootstrap book, or Chernick's "Bootstrap methods" book. I've only seen some side mentions in Ripley's Pattern recognition (when talking about stratified cross-validation), and Davison & Hinkley's bootstrap book when, on p. 304, they refer to some subsets having singular design matrices, and thus requiring stratification on covars. McLachlan (in his discriminant analysis book), on p. 347, differentiates between mixture sampling and separate sampling, but I can find a mention of wha...

Dear R community, Please, can you help me with a problem concerning bootstrap. I have a 20000 by 20 matrix. I want to define each row as a variable. Then using bootstrap to calculate standard errors, confidence intervals, and significance tests. How can I do from defining the variables to bootstrap analysis.. Thank you very much! Best Wishes Huangjian Peking University

Hello, I am new to R, and am having trouble getting the output I want from a stratified bootstrap. I didn't recieve a reply the first time I posted this question so I have tried to make it more clear. My data frame (denboot) is set up as follows: SITE cswa parea treat 1 BeanA 3 1.20 m 2 BeanBC 3 1.05 m 3 BeanD 1 0.93 m 4 BlackB 1 1.01

...amples taken from each year is equal to the number of data points from each year. Therefore I'm defining strata=year. boot1 <- boot(myfile, mat.fun, 5000, strata=myfile$year); boot1 Is this the correct way to do it or did I misunderstand the strata-argument? I checked in Davison, A.C. and Hinkley, D.V. (1997), but I'm still not quite sure. Thanks very much in advance for your help! Sincerely, Saskia Sandring _________________________________________________________________________ Saskia Sandring Avd. f??r v??xtekologi, Evolutionsbiologiskt centrum, Uppsala universitet Dept. of Plan...

[Resend with proper subject line] I am trying to compute bootstrap confidence intervals for a sample using R 2.5.1 for Windows. I can get "Normal", "Basic", "Percentile", "BCa" and "ABC" from boot.ci() and boot() in the Davison & Hinkley "boot" package. But I can't figure out how to use tilt.boot() to get the "tilting" confidence interval. Here's a program snippet: g = rgamma(N,shape=2,scale=3) #Generate a sample of N random deviates varf = function (x,i) { var(x[i]) } b = boot(g, varf, R=1000) boot....