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inference for customized regression in R?
3 messages · R. Michael Weylandt, Michael
Given the caveats Ted describes here: http://tolstoy.newcastle.edu.au/R/help/05/06/5992.html it seems that bootstrapping might be the only way to get (somewhat) credible prediction intervals: the boot package on CRAN can help to facilitate getting these. Here's some documentation for CI: http://www.statmethods.net/advstats/bootstrapping.html but you'll need to adopt it for a prediction interval, which might entail hacking boot.ci(). You might also see if this question, by someone who most certainly isn't you because cross-posting is discouraged, gets some answers: http://stats.stackexchange.com/questions/26277/how-to-bootstrap-prediction-intervals-for-customized-regression-models-in-r Michael Weylandt
On Wed, Apr 11, 2012 at 10:29 AM, Michael <comtech.usa at gmail.com> wrote:
Hi all, Are there functions in R that could help me do the following? We have a special type of regression which is called Geometric Mean Regression. We have done some search and found the following: https://stat.ethz.ch/pipermail/r-help/2011-July/285022.html The question is: how to do the statistical inference on GMR results? More specifically, we are looking for the prediction interval: Lets say we regress y1, y2, ..., yn onto x1, x2, ..., xn: we would like to know what's the prediction interval for a new data point: x_new=x1+x2+x3 (i.e. the new data point is the sum of the existing first three data points) In ordinary linear regression, we could derive prediction interval for an in-sample data point as well as a new data point... For our x_new=x1+x2+x3, we can derive formulas for the prediction interval. But for the above customized regression, how do we obtain the prediction intervals? ------------------------------ Are there functions in R that can help us do this? We are thinking of using bootstrapping, etc. Are there functions in R help us on this? Thanks a lot! ? ? ? ?[[alternative HTML version deleted]]
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