similar to: group definition for a bootstrap

Hello, I am trying to carry out a bootstrap analysis (using the boot package) on a table and cannot work out how to get the results I need! I have a table ("d2") with 4 columns: "ID_code", "Age", "Quarter" and "StomWt". Age (0-5) and Quarter (1-4) are my strata Therefore I wish to estimate the confidence intervals for the mean StomWt for each Age

hi, I would like to subsample the array c(1:200) at random into ten subsamples v1,v2,...,v10. I tried with to go progressively like this: > x<-c(1:200) > v1<-sample(x,20) > y<-x[-v1] > v2<-sample(y,20) and then I want to do: >x<-y[-v2] Error: subscript out of bounds.

R-help readers, I''m having a problem with an R script (see below), which regularly generates the error message, Error in start:(start + (sample.length - 1)) : NA/NaN argument , for which I am unsure of the cause. In essence, the script (below) generates the start and end points for random subsamples from along a vector (in reality a transect (of a given length,

Hello R-users, I am trying to obtain Type III SS for an ANOVA with subsampling. My design is slightly unbalanced with either 3 or 4 subsamples per replicate. The basic aov model would be: fit <- aov(y~x+Error(subsample)) But this gives Type I SS and not Type III. But, using the drop() option: drop1(fit, test="F") I get an error message: "Error in

Hello, I'm most grateful for your time to read this. I have a uber size 30GB file of 6 million records and 3000 (mostly categorical data) columns in csv format. I want to bootstrap subsamples for multinomial regression, but it's proving difficult even with my 64GB RAM in my machine and twice that swap file , the process becomes super slow and halts. I'm thinking about generating

Hello I apologise for the length of this entry but please bear with me. In short: I need a way of subsampling communities from all possible communities of n taxa taken 1:n at a time without having to calculate all possible combinations (because this gives me a memory error - using combn() or expand.grid() at least). Does anyone know of a function? Or can you help me edit the combn or

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

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

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

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 All, Anyone has some idea how to implement 632 estimator and leave-one out bootstraping method by using boot package. I know the bootstrap package has this function, but it sounds not very flexible for my project. Thanks, Jim

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

Hi all Forgive me, I'm a total R newbie, and this seems to be a straightforward simple bootstrap problem, but after a whole day of trying to figure out how to do it I'm ready to give up. Part of the problem is that every example and every help page seems to be about doing something more far more complex. I'm got a table with 40 columns and 750 rows. I sum all the values across the

Hallo everybody, I'm wondering whether it might be possible to speed up the following code: Error<-rnorm(10000000, mean=0, sd=0.05) estimate<-(log(1.1)-Error) DCF_korrigiert<-(1/(exp(1/(exp(0.5*(-estimate)^2/(0.05^2))*sqrt(2*pi/(0.05^2))*(1-pnorm(0,((-estimate)/(0.05^2)),sqrt(1/(0.05^2))))))-1)) D<-100000 Delta_ln<-rep(0,D) for(i in 1:D)

Hi, I wonder if someone can help me. I have built a gam model to predict the presence of cold water corals and am now trying to evaluate my model by splitting my dataset into training/test datasets. In an ideal world I would use the sample() function to randomly select rows of data for me so for example with 936 rows of data in my HH dataset I might say ss <- sample(nrow(HH), size =

Dear R users, This is more a statistical question rather than an R question. I'd appreciate it if you can give me some suggestions. I have a sample of a time series (sample size 500, fat tail in density). I am trying to calculate the Standard error of standard deviation of a sub-block-sample (sample size 250). I take 100 this kind of sub-block-sample, randomly. For these 100 subsamples, I

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

Dear R-experts, I am trying to bootstrap (and average) the median squared error evaluation metric for a robust regression. I can't get it. What is going wrong ? Here is the reproducible example. ############################# install.packages( "quantreg" ) library(quantreg) crp <-c(12,14,13,24,25,34,45,56,25,34,47,44,35,24,53,44,55,46,36,67) bmi

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