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Results tagged with bootstrap
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user 6479
The bootstrap is a resampling method to estimate the sampling distribution of a statistic.
4
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1
answer
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When using bootstrap analysis, which estimates should be reported, the original ones or the ...
I usually report the bootstrap estimate of the parameter (the mean of the bootstrap distribution), but from the theory I know that the bootstrap estimate should approach the original estimate if all $n … So I started to wonder that maybe in the results I should report the original parameter instead of the bootstrap one, together with the bootstrap derived variability statistics (eg, BCa CIs)? …
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2
votes
0
answers
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Bootstrap iteration as random effect
I have a theoretical question.
Would it make sense to replicate a dataset via bootstrapping and then perform a mixed effect analysis using the data from all iterations, specifying the specific iterat …
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2
votes
1
answer
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Can't .632+ rule be computed for any kind of outcome and prediction score?
It seems that the R packages I found around for computing the .632+ estimation of prediction error work only with categorical outcomes.
Why is that? Looking at the formulas in Efron 1997 paper it see …
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6
votes
1
answer
671
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How to deal with missing coefficients while bootstrapping regressions
I'm using R boot() function to perform regression bootstrapping.
When boot() resamples my data, can happen that some coefficients are missing, especially in the case of factor variables with many cas …
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20
votes
1
answer
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Bootstrap methodology. Why resample "with replacement" instead of random subsampling?
The bootstrap method has seen a great diffusion in the last years, I also use it a lot, especially because the reasoning behind is quite intuitive.
But that's one thing I don't understand. …
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3
votes
1
answer
474
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Correlation between bootstrap distribution of coefficients in multivariabile glm
I'm investigating bootstrap properties lately. … The picture on the left shows the correlation matrix between the bootstrap distribution of each couple of predictors. …
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2
votes
1
answer
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Quantum computing and resampling techniques
For example one could perform bootstrap or cross validation using all possible combinations instead of relying on chance, hoping to find the right compromise between sampling bias and computation time. …
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2
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1
answer
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How to interpret a significant effect in a multivariable when a factor is represented by jus...
Furthermore the fact that bootstrapping increases the frequency of significant singleton effects is a misbehave of bootstrap (type 1 error) or of the analytics methods (type 2 error)? …
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3
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0
answers
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Bootstrap logistic regression with rare events and rare outcomes and rare predictors
I am recently using bootstrap for statistical inference and confidence interval building in the setting of regression, especially logistic regression. … The reported 95% CI are the bootstrap accelerated, bias adjusted confidence intervals [DiCiccio, T.J. and Efron B. (1996) Bootstrap confidence intervals. …
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4
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Creating a bootstrap null (H0) distribution. Investigating alternatives
I'm investigating the possibility of creating a non parametric bootstrap null distribution for hypothesis testing in multivariable regression analysis. … Local permutation: Permute the variable AFTER bootstrap resampling of observations.
Global resample: Resample with replacement the variable BEFORE apply bootstrap resampling to the data set. …
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