Timeline for How many observations are taken for a pseudo-sample when bootstrapping?
Current License: CC BY-SA 3.0
15 events
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| Aug 14, 2013 at 0:49 | comment | added | Glen_b | However, it would also serve as a basic answer to the suggested question. If you're satisfied with this one as an answer to your original one, asking a new question is reasonable. | |
| Aug 14, 2013 at 0:43 | vote | accept | Young | ||
| Aug 14, 2013 at 0:42 | comment | added | Young | Thanks Glen, I guess I should make a new question rather than modifying it as you made it very clear what bootstrapping does above and below. Thanks for editing. | |
| Aug 14, 2013 at 0:26 | answer | added | Glen_b | timeline score: 2 | |
| Aug 14, 2013 at 0:04 | comment | added | Glen_b |
Young, I suggest you explicitly modify your question to relate directly to what you're doing ... such as "How would I bootstrap a correlation?" or even asking about the statistical problem you're trying to solve (which appears to be one about the sampling properties of correlations) and then at the end of your general question, add some specific parts asking about doing it using boot.
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| Aug 14, 2013 at 0:02 | comment | added | Glen_b | Yes, that's what bootstrapping does. What you described at the start of that most recent comment sounds more like an attempt at cross validation | |
| Aug 13, 2013 at 23:59 | comment | added | Young | @Glen_b Yes, I need to know both "how does it work" and "how do you the arguments?". I wanted to know how robust my data set is in terms of correlations. I randomly took 65% of the data and bootstrapped it to see if I still get the same or similar correlations coefficients. I think now I know a little better about bootstrapping thanks to you. So this argument "R" is the number of samples to take. If the number of data points in actual data set is only 200 and R is 1000, "boot" take data point randomly 1000 times from 200 data points. I hope this is correct. | |
| Aug 13, 2013 at 23:51 | comment | added | Glen_b | You might find the explanation in the fourth paragraph here of some value. | |
| S Aug 13, 2013 at 23:47 | history | edited | Glen_b | CC BY-SA 3.0 |
attempted to clarify the question by removing conflation of terms 'observation' and 'sample'
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| Aug 13, 2013 at 23:46 | review | Suggested edits | |||
| S Aug 13, 2013 at 23:47 | |||||
| Aug 13, 2013 at 23:43 | review | Close votes | |||
| Aug 14, 2013 at 17:04 | |||||
| Aug 13, 2013 at 23:41 | comment | added | Glen_b | Is your real question actually just 'How does bootstrapping work?' rather than 'How do I use the arguments of this function in R?' --- To hopefully speed this up I'm going to make a guess what you mean and edit your question to one that makes sense, and if I am wrong, please revert it (it takes two mouse clicks to revert). | |
| Aug 13, 2013 at 23:36 | comment | added | Glen_b |
I have no idea what you're asking now. Perhaps you should say what you think the bootstrap is. I highly recommend reading the book that the boot package goes with. Are you confusing the terms 'observation' (a data point for a single observational unit, like a person - possibly with observations on several variables) with 'sample' (a collection of such observations)? Please note that when you resample with the bootstrap you take your pseudo-samples of size $n$; in the notation of the function, you take R such samples. You don't need to specify $n$ because it can see how big the original is.
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| Aug 13, 2013 at 23:34 | comment | added | Young | Thanks, @Glen_b It seems that I misunderstand a concept of bootstrapping.... I thought "R" is the number of bootstrapping (i.e. the number of times the samples are taken, not the number of samples that are taken.). If R is the number of samples that are taken, how do you set up the number of times the samples are taken? | |
| Aug 13, 2013 at 23:13 | history | asked | Young | CC BY-SA 3.0 |