similar to: memory and bootstrapping

Could someone help me on how to correctly try to correct this error message arning : BCa Intervals used Extreme Quantiles Some BCa intervals may be unstable Warning message: Extreme Order Statistics used as Endpoints in: norm.inter(t, adj.alpha) Regards IF [[alternative HTML version deleted]]

HI everyone, I try to get some bootstrap CIs for coefficients obtained by quantile regression. I have influencial values and thus switched to quantreg.. The data is clustered and within clusters the variance of my DV = 0.. Is this sensible for the below data? And what about the warnings? Thanks in advance for any guidance, Kay > dput(d) structure(list(Porenfläche = c(4990L, 7002L, 7558L,

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 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

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

Hello all, This question concerns the function Dotplot from the Hmisc package. My aim is to compare values between groups in each panel of the Dotplot, with the values of different groups clearly distinguishable by different symbols. All lines and symbols should be coloured in black. Before adding the panel function to the Dotplot, the groups behaved as desired and were marked by different

In the boot package,consider a scalar function to boot. > estimator <- function(x, d) { + mean(x[d]) + } > > data <- city$u > b <- boot(data, estimator, R=1000) > b$t0 [1] 64 > ci <- boot.ci(b, type=c("bca"), conf=.95) > ci$bca conf [1,] 0.95 49.44 991.39 36.78807 110.0254 Now if I want estimators to return a vector,E.g. it's {c(mean(x[d]),

Dear R users, I am new to R. I would like to calculate bootstrap confidence intervals using the BCa method for a parameter of interest. My situation is this: I already have a set of 1000 bootstrap replicates created from my original data set. I have already calculated the statistic of interest for each bootstrap replicate, and have also calculated the mean for this statistic across all the

Hello there, I have a linear regression model for which I estimated heteroskedasticity-robust (Huber-White) standard errors using the coeftest function in the lmtest-package. Now I would like to inspect the predicted values of the dependent variable for particular groups and include a confidence interval for this prediction. My question: is it possible to estimate confidence intervals for the

hi there, I have a list of 5 identical dataframes: mydf <- data.frame(x=c(1:5), y=c(21:25)) mylist <- rep(list(mydf),5) and a factor variable with 5 levels: foo <- c(letters[1:5]) foo <- as.factor(foo) Question: I'd like to add a new variable to each dataframe in the list, each containing only one level of the factor variable. So mylist[[1]] should have a new variable z

I tried to reproduce a result from a former colleague which he got with S-plus bootstrap method. I don't have S-plus at hand. In R, there are 2 packages related to bootstrap method, bootstrap and boot. The former has a function called 'bootstrap' but this does not seem to conform either to the function used in S-plus nor to that described in MASS, 3d ed., p.144. The latter seems to be

Hi there, Could someone help me with the following programming problem..? I have written a function that works for my intended purpose, but it is quite closely tied to a particular dataframe and the names of the variables in this dataframe. However, I'd like to use the same function for different dataframes and variables. My problem is that I'm not quite sure how to tell my function in

I'm confused about name spaces. This morning I installed the boot package because I wanted to look at bca.ci. So I did library(boot), but then I had, > bca.ci Error: Object "bca.ci" not found I had a look in the boot R directory and bca.ci was there as expected. So then I took a look at the NAMESPACE file for the boot package and saw that bca.ci wasn't exported. I tried

Hello, Much clearer now, thanks. It's a matter of changing the function boot calls to return the predicted values at the point of interess, education = 50, income = 75. I have changed the way the function uses the indices a bit, the result is the same, it's just the way I usually do it. pred.duncan.function <- function(data, indices) { mod <- lm(prestige ~ education +

>From: Jeff Cohen Date: Wed, 26 Jan 2005 19:47:44 -0800 > >Fixed. Yes, now it isn't the path. I've recorded this trace: ------------------------- llvm[3]: Building Debug Bytecode Archive libc.bca /bin/rm -f /C/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca /C/projects/build/MinGW/llvm-4-1/Debug/bin/llvm-ar rcsf /C/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca

Good Morning, I'm having what I hope to be a simple problem. I am generating bootstrap confidence intervals using package (boot) - which works perfectly. The issue I am having is getting the results into a format which I can write out to a database. To be clear I am having no problems generating the results, I just need to convert the format of the results such that I can store the results in

On Thu, 2005-01-27 at 13:16, Henrik Bach wrote: > c:\projects\build\MinGW\llvm-4-1\Debug\bin\llvm-ar.exe: > c:/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca-000000: Can't destroy > file (hb:2): The process cannot access the file because it is being used by > another process. > make[3]: *** [/C/projects/build/MinGW/llvm-4-1/Debug/lib/libc.bca] Error 2 >

Hi all: I get the following error message that I am not able to resolve. Error in if (const(t, min(1e-08, mean(t)/1e+06))) { : missing value where TRUE/FALSE needed It appears right before the last data.frame statement. Below is the program that simulates data from one way random effects model and then computes normality and bootstrap confidence interval for

Hello Rui, Thanks for your helpful suggestions. Just for illustration, let's use the well known Duncan dataset of prestige vs education + income that is contained in the "car" package. Suppose I wish to use boot function to bootstrap a linear regression of prestige ~ education + income and use the following script: duncan.function <- function(data, indices) {data =

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