similar to: sort of OT: bootstrap tutorial

Sometimes one might like to obtain pointwise bootstrap bias-corrected, accelerated (BCA) confidence intervals for a large number of statistics computed from a single dataset. For instance, one might like to get (so as to plot graphically) bootstrap confidence bands for the fitted values in a regression model. (Example: Chiu S et al., Early Acceleration of Head Circumference in Children with

Dear all, The other day I was reading this post [1] that slightly surprised me: "To reject the null of no correlation, an hypothsis test based on the normal distribution. If normality is not the base assumption your working from then p-values, significance tests and conf. intervals dont mean much (the value of the coefficient is not reliable) " (BOB SAMOHYL). To me this implied that in

Dear experts, I am asking for help with a question regarding to stratified bootstrap. My dataset is a longitudinal dataset (3 measurements per person at year 1, 4 and 7) composed of multiple clinic centers and multiple participants within each clinic. It has missing values. I want to do a bootstrap to find the standard errors and confidence intervals for my variance components. My model is a

Hello, I learnt there's an advanced R/Splus course in Boston this january. Anyone got the announcement? please kindly forward it to me. Best, Eugene

Dear R useres, I'm interested in getting a series of time-varying correlation, simply between two random variables. Could you please introduce a package to do this task? Thank you so much for any help. Amir --------------------------------- Don't pick lemons. [[alternative HTML version deleted]]

Hi, consider this one as an FYI, or a seed for further discussion. I am aware that many traps on sample() have been reported over the years. I know that these are also documents in help("sample"). Still I got bitten by this while writing sample(units, size=length(units)); where 'units' is an index (positive integer) vector. It works in all cases as expected (=I expect)

Hi I was wondering if there is a permutation test available in R for linear models with continuous dependent covariates. I want to do a test like the one shown here. bmi<-rnorm(100,25) x<-c(rep(0,75),rep(1,25)) y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x H0<-lm(y~1+x+bmi) H1<-lm(y~1+x+bmi+x*bmi) anova(H0,H1) summary(lm(y~1+x+bmi)) But I want to use permutation testing to

Hello all, I am trying to run a two sample t-test on a matrix which is a 196002*22 matrix. I want to run the t-test, row-wise, with the first 11 columns being a part of the first group and columns 12-22 being a part of the second group. I tried running something like (temp.matrix being my 196002*22 matrix) t.test(temp.matrix[,1:11],temp.matrix[,12:22],paired=TRUE) or somthing like

I suggest a simple enhancement to segments() and arrows() to facilitate drawing horizontal and vertical segments -- set default values for the second x and y arguments equal to the first set. This is handy, especially when the expressions for coordinates are long. Compare: Segments: < function (x0, y0, x1 = x0, y1 = y0, col = par("fg"), lty = par("lty"), --- > function

Dear R experts, I have defined a class "myclass" and would like the slots to be extractable not only by "@" but also by "$". I now try to write a method for "$" that simply executes the request object at slotname, whenever someone calls object$slotname for any object of class "myclass". I don't manage to find out how I can provide this

Hi there, I want to generate different samples using the followindg code: g<-sample(LETTERS[1:2], 24, replace=T) How can I specify that I need 12 "A"s and 12 "B"s? Thank you, Judith ____________________________________________________________________________________ Be a better friend, newshound, and

Hi [R-2.6.0, macOSX 10.4.10]. The helppage says that rowSums() and colSums() are equivalent to 'apply' with 'FUN = sum'. But I came across this: > a <- matrix(1:30,5,6) > is.integer(apply(a,1,sum)) [1] TRUE > is.integer(rowSums(a)) [1] FALSE > so rowSums() returns a float. Why is this? -- Robin Hankin Uncertainty Analyst National Oceanography Centre,

Hi dear all, Can someone help me about detection of outliers using jackknife after bootstrap algorithm? -- View this message in context: http://r.789695.n4.nabble.com/jackknife-after-bootstrap-tp3041634p3041634.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]

Hi! When I apply the lars (least-angle-regression) method to my data (3655 features, only 355 data points, no I did not mistype), I observe a strange behaviour: 1) The beta values tend to grow into real high values quite fast up to a point where they overflow and get negative. The overflow is not a problem, I don't need the last part of the analysis anyway, but why do they just

Hi everyone! In a package I'm developing, I have created a custom function to get jackknife standard errors for the parameters of a gnm model (which is essentially the same as a glm model for this issue). I'd like to add support for bootstrap using package boot, but I couldn't find how to proceed. The problem is, my data is a table object. Thus, I don't have one individual per

Are there any packages in R that reproduce the package "resample" of S-Plus? The sample() function in R doesn't provide equivalent flexibility of bootstrap() and bootstrap2(). ================================================================ Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: ral at lcfltd.com Least Cost Formulations, Ltd. URL: http://lcfltd.com/ 824

Hello; Our survey is structured as : To be investigated area is divided into 6 regions, within each region, one urban community and one rural community are randomly selected, then samples are randomly drawn from each selected uran and rural community. The problems is that in urban/rural stratum, we only have one sample. In this case, how to do bootstrap? Any comments or hints are greatly

I've been playing with passing arguments to .C(), and found that replacing as.double(x) with if(is.double(x)) x else as.double(x) saves time and avoids one copy, in the case that x is already double. I suggest modifying as.double to avoid the extra copy and just return x, when x is already double. Similarly for as.integer, etc. [[alternative HTML version deleted]]

I apologize for this post. I am new to R (two days) and I have tried and tried to calculated confidence intervals for medians. Can someone help me? Here is my data: institution1 0.21 0.16 0.32 0.69 1.15 0.9 0.87 0.87 0.73 The first four observations compose group 1 and observations 5 through 9 compose group 2. I would like to create a bootstrapped 90% confidence interval on the difference of

Hello, How can I do a cross validation in R? Thank You!