From: Tim Hesterberg <timh_at_insightful.com>

Date: Thu, 06 Dec 2007 09:08:20 -0800

R-help_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 06 Dec 2007 - 17:12:14 GMT

Date: Thu, 06 Dec 2007 09:08:20 -0800

It sounds like you should sample x and y together using the block bootstrap. If you have the usual situation, x and y in columns and observations in rows, then sample blocks of rows.

Even though observations in y are independent, you would take advantage of that only for bootstrapping statistics that depend only on y.

The answer to your second question is the same as the first - sample blocks of observations, keeping x and y together.

Tim Hesterberg

>Hello.

*>
**>I have got two problems in bootstrapping from
**>dependent data sets.
**>
**>Given two time-series x and y. Both consisting of n
**>observations with x consisting of dependent and y
**>consisting of independent observations over time. Also
**>assume, that the optimal block-length l is given.
**>
**>To obtain my bootstrap sample, I have to draw
**>pairwise, but there is the problem of dependence of
**>the x-observations and so if I draw the third
**>observation of y, I cannot simply draw the third
**>observation of x (to retain the serial correlation
**>structure between x and y), because I devided x into
**>blocks of length l and I have to draw blocks, then I
**>draw from x.
**>
**>1.
**>How can I compute a bootstrap sample of the
**>correlation coefficient between x and y with respect
**>to the dependence in time-series of x?
**>
**>2.
**>How does it look like, if x and y both consist of
**>dependent observations?
**>
**>
**>
**>I hope you can help me. I got really stuck with this
**>problem.
**>
**>Sincerly
**>Klein.
*

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