# Questions tagged [bootstrap]

The bootstrap is a resampling method to estimate the sampling distribution of a statistic.

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### Hypothesis testing for difference in medians vs. median difference

I found this post saying that one should test for the median difference instead of the difference in medians, in particular if the data is skewed: http://onbiostatistics.blogspot.com/2015/12/median-of-...
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### Bootstrapping the t-Test

my problem is of practical nature regarding bootstrapping the t-Test. My approach is to code a function which resamples the data vector and calculates the t-statistic for each new (resampled) vector. ...
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### Bootstrapping in logistic regression with sparse binary variable

I would like to estimate the probability of a relation between two entities. The data set includes information of many relations between many entities, and information on covariates for each entity. ...
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### How can bootstrapping help in meeting assumptions of linear regression

I was reading through my stat book and it was written that bootstrapping can relax the distribution assumptions for linear regression generalizability. I do not quite understand what assumptions we ...
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### What is the point of using bootstrapping in logistic regression of sentiment analysis?

Apologies if the title is a bit ambiguous. Let's say I am trying to use logistic regression to predict whether a book review is positive or negative using the bag of words approach. My homework asks ...
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### Safety stock calculations using Intermittent Bootstrap

Together with fellow students, I’m working on an assignment to calculate safety stock levels in case of intermittent demand. We’re already able to simulate the demand like in the paper of Willemain, ...
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### Using Bootstrap for an arbitrary statistics

I know that we can use bootstrap to get confident intervals for mean and quantiles (like medians). However I have 2 questions: 1/ The confident interval for median we get from bootstrap, can we ...
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### Good proportion of training data to get prediction interval using bootstrap

I am trying to get prediction intervals thanks to bootstrap: I train 1000 linear regressions with different subsets of my training data. Say I have 1,000,000 rows in my dataset, what would be a good ...
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### Implications of Different Bootstrap Procedures for Estimating Difference in Means

I'm having trouble understanding the difference between two bootstrap procedures to evaluate the difference in means between two samples. As an example, consider the following scenario: My goal is to ...
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### Running a simulation: replications or bootstrap?

I draw $n$ iid random draws from a univariate Gaussian distribution. My goal is to estimate the density $f$ using a nonparametric density estimation approach. To add a measure of uncertainty, I want ...
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### Bootstrapped distribution of RMSE

I have two distributions of volume conservation factors (VCF) Generic and Generic Masked that I want to compare. The VCF being optimal if equal to 1, I want to show that one distribution is ...
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### Bootstrapping Confidence intervals for model coefficients in R [closed]

I'm trying to create some confidence intervals for my regression coefficients via the non-parametric bootstrapping method. however, as my code currently stands, I'm only receiving a bootstrapped CI ...
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### Model Comparison Tests with Bootstrapped Models

I've found myself in a catch-22 of wanting to conduct model comparison tests (like the Likelihood Ratio Test) but having to accommodate non-normal data. I know the LR test is invalid with Robust ...
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### Hypothesis testing with composite populations of unequal size and variance

I am trying to test whether two populations have different means. Let's call the populations "Glaciated" and "Unglaciated." Each population comprises data collected at a number of rivers (9 for ...
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### Multiple R-squared from bootstrap in R

I am fairly new to R and am having issues with my bootstrapped linear model. I'm using non-parametric case re-sampling to account for some skewed variables. Here is what I have done so far: ...
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### Are positively biased bootstrap-derived GAM predictions indicative of model issues?

all, I am using a negative binomial GAM fitted with mgcv::gam to estimate counts for new data, and I wanted to use bootstrapping to find a 95% confidence interval for point estimates. In my ...
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### Choice of statistic for Bootstrap confidence intervals

I am learning about the bootstrap (from this book) and have some questions about best practices. The usual approach seems to be to draw bootstrap samples of the same size as the observed sample. ...
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### confidence interval for mean based on small sample when CLT does not hold

I have looked at similar questions but could not find an satisfactory answer. Please forgive if I'm wrong. I have a small sample (n = 24) and use the sample mean as estimator of the true mean. I want ...
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### Completely asymmetrical confidence intervals (Bootstrapping)

I have calculated a Kendall's tau-b partial correlation coefficient (N > 2000). I have calculated a bootstrap confidence interval around the estimate, but what I find is that the confidence interval ...
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### Is this an appropriate use of bootstrapping? variability in a fleet's fuel economy

I have a data set consisting of the make and models of a diverse fleet of vehicles (e.g. 100 Honda Civics, 200 Ford F150s, 10 Tesla Model 3s). My goal is to estimate the average fuel economy of the ...
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### Confidence interval of bootstrapped difference of means

I am attempting to calculate a confidence interval for a difference in 2 populations by means of bootstrapping in order to compare this to an interval calculated via normal theory. I am getting stuck ...
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### Nonparametric bootstrap: Circular reasoning behind colleague's comments?

I have developed an iterative stochastic optimization search procedure that improves on a single initial guess until some desired threshold is reached, similar to how simulated annealing proceeds ...
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### Bootstrap test for comparing two variances

How to use bootstrap to test the equality of two variances?
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### Probability of a value given a dataset

I am trying to figure out a way to determine how extreme a particular value is from single variable, when the distribution of the variable is unknown. I have tried doing this with a kind of boot-...
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### Robust regression vs bootstrapping of confidence intervals

In multiple regression, when the independent variable is not normally distributed and the dependent variable is not normally distributed, is bootstrapping of the confidence intervals or robust ...
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### Why ever use a quasipoisson model instead of bootstrapped poisson GLM?

A poisson GLM and a quasipoisson regression model will given identical point estimates for the beta parameter of the linear predictor. The quasipoisson model is typically used when there is ...
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### Efron bootstrapped confidence intervals does not include corrected value of metric

So in order to correct for optimism on my model I have used the Efron bootstrapping to calculate the optimism to correct my apparent value of several validation metrics for my model (repeated 500 ...