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Results tagged with bootstrap
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user 7290
The bootstrap is a resampling method to estimate the sampling distribution of a statistic.
2
votes
Bootstrapping and Kolmogorov-Smirnov
The thing to recognize here is that all of your bootsamples come from the same population. That is, the null hypothesis obtains here. Bear in mind that under the null hypothesis, the $p$-value is di …
30
votes
Accepted
What is the meaning of a confidence interval taken from bootstrapped resamples?
For a somewhat mathematical explanation of the bootstrap, see @StasK's answer here: Explaining to laypeople why bootstrapping works . …
3
votes
Accepted
Bootstrapping where each sample size is the same size as the whole sample?
The bootstrap gives us a sense of what the sampling distribution of the mean from our sample-as-population would look like. …
20
votes
How do I compare bootstrapped regression slopes?
When you bootstrap, there is effectively no limit to the number of `bootsamples' you take; in fact you get a better approximation to the sampling distribution the more bootsamples you take. … Regarding the first point, you may not need to bootstrap in your situation; regarding the second point, bootstrapping the slope is perfectly fine. …
6
votes
Accepted
Bootstrap two-sample t test
Next, recognize that there are several ways to bootstrap: e.g., you can bootstrap your data directly or bootstrap a test statistic, you can bootstrap your sampling distribution or a null distribution, … (However, you should re-do your bootstrap using the correct $n_j$s before you go with this result.) …
6
votes
Accepted
Does using bootstrapping change how you deal with problems of Type I errors when testing mul...
I also don't follow your situation 100%, but I suspect it doesn't matter. The problem of multiple comparisons arises simply due to the mathematics of looking at lots of random things. That is, each …
155
votes
Explaining to laypeople why bootstrapping works
+1 to @ConjugatePrior, I just want to bring out one point which is implicit in his answer. The question asks, "if we are resampling from our sample, how is it that we are learning something about the …
1
vote
Bootstrap, Monte Carlo
Perhaps they only want you to do this for the Monte Carlo, and not the bootstrap? That isn't a requirement I would have for an exercise, though. …
3
votes
Inconsistent outcomes of boostraped hypothesis tests on max and median
It works progressively less well as you try to bootstrap quantiles towards the tails of your distribution. It necessarily fails when trying to bootstrap the minimum value or the maximum value. … It may help you to read @Cardinal's excellent answer here: What are examples where a "naive bootstrap" fails?, which explicitly discusses bootstrapping the max. …
2
votes
Logistic regression with bootstrap, how to interpret high standard errors and choose coeffic...
I don't follow your code, you call your data different things in different places, I don't see your function being used anywhere, etc. Setting that aside, I'm not sure there is a big problem with you …
46
votes
Accepted
Bootstrap vs. jackknife
However, the bootstrap provides information about the whole sampling distribution, and can offer greater precision. …
6
votes
Bootstrapping a t-test in R
For the qq-plot for the t-distribution, I used the df that corresponds to equal variances, which won't quite match the bootstrap (where each iteration will have a different effective df). …
2
votes
Accepted
Probability of an unknown distribution
With more than $7,\!000$ observations, you are probably safe to use the proportion of observations at a given value as an estimate of the probability of drawing that value at random from the populatio …