similar to: BCa-intervals not defined in boot.ci() for tsboot() -> package: boot

Dear all, Does someone know an R function implementing the method of Sison and Glaz (1995) (see full ref below) for computing Simultaneous confidence intervals for multinomial proportions? As alternative method, I think to boostrap the mean of each proportion and get in that way confidence interval of the mean. I observed 21 times a response that could be one out of 8 categories

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

I'm using R 2.15.1 on a 64-bit machine with Windows 7 Home Premium. Sample problem (screwy subscripted syntax is a relic of edited down a more complex script): > N <- 25 > s <- rlnorm(N, 0, 1) > require("boot") Loading required package: boot > v <- NULL # hold sample variance estimates > i <- 1 > v[i] <- var(s) # get sample variance >

Dear R-Experts, Thanks to Prof. Bonnett, I have got an R script working to calculate confidence intervals around the semipartial correlation coefficients. Now, I would like to calculate BCa bootstrap CIs using the boot library and the boot.ci(results, type="all") function. How could I modify my R script (here below reproducible example) to get the BCa bootstrap CIs ? CIsemipartcorr

Dear All, I am trying to use the bca.ci function on a boot.out object which consists a few NaN's and I want to ignore those NaN's, and get a ci only for the "normal" values. boot.out$t has R number of values for 3000 different statistics, so when I use boot.ci(boot.out, index=i) and i happens to be a column in boot.out$t with some NaN's in there I get an error message. I

i was searching for the source of bca.ci, a function of the package boot. I tried require(boot, keep.source=TRUE) but again the source was not viewable. How should i do? Best regards Meinhard Ploner ---------------- PS > version _ platform i386-apple-darwin8.8.1 arch i386 os darwin8.8.1 system i386, darwin8.8.1 status major 2

Dear R-users, tsboot fails when I try to perform a block bootstrap on seaKen (package wq): these commands: require(wq) require(datasets) boot.block.sen <- function(data){seaKen(data)[[1]]} tsboot(sunspot.month, boot.block.sen, R=1999, l=12, sim="fixed") return: Error in seaKen(data) : x must be a 'ts' Any suggestion on how might I change seaKen in order to use it with

I'm trying to bootstrap some regression coefficients so that I can estimate confidence intervals, but boot is not producing results. Can anybody suggest what I'm doing wrong here? > SpecPress <- ts(rnorm(501)) > Returns <- ts(rnorm(501)) > BootData <- data.frame(cbind(SpecPress, Returns)) > boot.specpress <- function(data, indices, maxit=20){ + data <-

I like to bootstrap regression models, saving the entire set of bootstrapped regression coefficients for later use so that I can get confidence limits for a whole set of contrasts derived from the coefficients. I'm finding that ordinary bootstrap percentile confidence limits can provide poor coverage for odds ratios for binary logistic models with small N. So I'm exploring BCa confidence

Does anyone know how p-values can be generated if tsboot (stationary bootstrap) for time series is performed? That would be of great help. Thanks a lot for your comments. Markus [[alternative HTML version deleted]]

Hi everyone, I use the boot package within the MBESS package to automate much of the hard part for folks interested in performing a (simple) mediation model. The function mediation() works well, except for a (probably) unrealistic artificial data set. When I apply the bootstrap I sometimes get: Error in t.star[r, ] <- res[[r]] which is (I think) due to Inf and -Inf and NaN values produced for

Dear List, Couple of issues while using functions from ?BCA? library: 1. I am trying to use ?lift.chart? function from ?BCA? library, but facing issues while using model where model formula is passed as formula object in glm. When model formula is written as text, then it works fine. In my case input variables and target variables are going to change dynamically, so have to used formula as

Dear List I have run into some problems with boot.ci from package boot. When I try to obtain a confidence interval of type bca, boot.ci() returns the following error when the data set i large: Error in bca.ci(boot.out, conf, index[1L], L = L, t = t.o, t0 = t0.o, : estimated adjustment 'a' is NA Below is an example that produces the above mentioned error on my machine. library(boot)

Fritz, I have slightly adapted (didn't work before) "tsboot" from the "boot" library to the current time series conventions of R. The following patch will do that. I suggest to apply this patch to the file "boot/R/bootfuns.q" of the "boot" library at CRAN. best Adrian --- bootfuns.orig.q Thu Dec 9 10:07:23 1999 +++ bootfuns.q Thu Dec 9 10:06:51 1999

Fritz, I have slightly adapted (didn't work before) "tsboot" from the "boot" library to the current time series conventions of R. The following patch will do that. I suggest to apply this patch to the file "boot/R/bootfuns.q" of the "boot" library at CRAN. best Adrian --- bootfuns.orig.q Thu Dec 9 10:07:23 1999 +++ bootfuns.q Thu Dec 9 10:06:51 1999

Hello, I have a question regarding bootstrap confidence intervals. Suppose we have a data set consisting of single measurements, and that the measurements are independent but the distribution is unknown. If we want a confidence interval for the population mean, when should a bootstrap confidence interval be preferred over the elementary t interval? I was hoping the answer would be

Dear all, I've a problem with bootstarp package... I want to bootstrap correlation ratio of some data. my code is: f<-function(d) cov(d$x,d$y)/sqrt(var(x)*var(y)) boot(d,f,R) As a result I got an error: Error in statistic(data, original, ...) : unused argument(s) (.. .) d is a data.frame containing two vectors with labels x and y. Also, another thing I have problem

Dear boot.ers, I ran a small program for training purposes and ended with problems in boot.ci bush <- c(rep(1, 840), rep(0, 660)) > f.mean <- function(y, id) {mean(y[id])} > bushB <- boot(bush, f.mean, 1000) > boot.ci(bushB, conf = 0.95, type = c('perc', 'bca')) Error in bca.ci(boot.out, conf, index[1], L = L, t = t.o, t0 = t0.o, h = h, : estimated

I'm using R 2.15.1 on a 64-bit machine with Windows 7 Home Premium and package 'boot'. I've found that using a number of bootstrap resamples in boot() that is less than the number of data results in a fatal error. Once the number of resamples meets or exceeds the number of data, the error disappears. Sample problem (screwy subscripted syntax is a relic of edited down a more

Dear R users, I am getting following error while using boot.ci. I have int.inc function with 20000 values. I am generating CI for the sample estimate. *> med <- function(x,i) median(x[i])* *> b1 <- boot(int.inc,med,2)* *> ci.out <- boot.ci(b1,conf = c(0.95),type = c("bca"))* *Error: cannot allocate vector of size 1.5 Gb* * * It would be very helpful to get some