Linked Questions

5
votes
0answers
112 views

When should one avoid bootstrapping? [duplicate]

Possible Duplicate: What are examples where a “naive bootstrap” fails? Perhaps this question will turn out to be a bit soft, but I think it may have a hard answer. Feel free to move ...
315
votes
11answers
139k views

Explaining to laypeople why bootstrapping works

I recently used bootstrapping to estimate confidence intervals for a project. Someone who doesn't know much about statistics recently asked me to explain why bootstrapping works, i.e., why is it that ...
60
votes
4answers
18k views

Assumptions regarding bootstrap estimates of uncertainty

I appreciate the usefulness of the bootstrap in obtaining uncertainty estimates, but one thing that's always bothered me about it is that the distribution corresponding to those estimates is the ...
30
votes
4answers
4k views

Is it true that the percentile bootstrap should never be used?

In the MIT OpenCourseWare notes for 18.05 Introduction to Probability and Statistics, Spring 2014 (currently available here), it states: The bootstrap percentile method is appealing due to its ...
13
votes
1answer
2k views

Is bootstrapping a valid method to assess the uncertainty of the median estimate?

Bootstrapping works well to access the uncertainty in the mean estimate, however I remember reading somewhere the bootstrap does not do a good job in assessing the uncertainty in quantile estimates (...
8
votes
2answers
383 views

Recommended reading for understanding when the bootstrap will fail?

It is known that the bootstrap can fail. I read in Section 6 of Bickel and Freedman (1981) that the bootstrap fails when you wan to use it to evaluate the MLE for estimating the parameter of a ...
4
votes
1answer
2k views

Estimating quantiles by bootstrap

It's known that one shouldn't use bootstrap to estimate minimum and maximum of the distribution which are quantiles. I have heard the reasoning that quantiles cannot be bootstrapped because quantile ...
2
votes
1answer
2k views

How to estimate true value and 95% bands when distribution is asymmetrical?

I have a set of results of independent measurements of some physical quantity. As an example I give here real expermental data on methanol refractive index at 25 degrees Celsius published in ...
5
votes
1answer
645 views

Bootstrap method- downsides

Can you tell me when doesnt the bootstrap method work? I know that could be outliers, but is there any particular distribution when it doesn't work?
5
votes
2answers
227 views

How to statistically test upper bound

Suppose a theory claims that a random variable $R$ (of unknown distribution $F$) must satisfy a certian upper bound $R < c$ (where $c$ is known constant). Suppose I perform a set of measurements $...
2
votes
1answer
220 views

What characteristics of the distribution of a test statistic can be inferred using a bootstrap?

Setup: Let $p_n(x) = \mathbb{P}(S_n \leq x)$ and let $p_n^*(x) = \mathbb{P}^*(S_n^* - S_n \leq x)$, where $S_n$ is some zero-mean test statistic that can validly be bootstrapped, eg a sample mean, and ...
2
votes
1answer
130 views

Inconsistent outcomes of boostraped hypothesis tests on max and median

I am trying to make an hypothesis test using bootstrapping. I compute a quantity Q from a sample set (the exact calculation should not be relevant, but let's say ...
1
vote
0answers
195 views

Confidence interval for maximum value in velocity time series

I have a time series of velocity values, which is structured into two periods. The first period describes the baseline velocity ("pre"). At the beginning of the second period ("post"), a stimulus is ...
1
vote
1answer
78 views

Estimating the true distributions from a sample of distributions

I am having a hard time formulating the following problem. Consider a company that runs a survey across several cities in the US to estimate the percentage of right-handed people and left-handed ...
0
votes
0answers
43 views

Why don't we always use bootstrapping? [duplicate]

Bootstrapping is such a great technique for ensuring that noise is correctly accounted for. Why don't we always use bootstrapping for all statistical and machine learning techniques? It seems to ...