Comments on: Tues Mar 13 http://www.stat.cmu.edu/~kass/smnp/?p=101 Thu, 26 Apr 2012 14:07:02 +0000 hourly 1 http://wordpress.org/?v=3.0.4 By: Thomas Kraynak http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-195 Thomas Kraynak Tue, 13 Mar 2012 13:30:26 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-195 Can you go more into detail how the unknown φ is acquired? The text seems to give two pretty distinct methods of using this value (parameter vector φ = f(θ) or using the distribution's median) and I'm having trouble deciding when to use each method. Can you go more into detail how the unknown φ is acquired? The text seems to give two pretty distinct methods of using this value (parameter vector φ = f(θ) or using the distribution’s median) and I’m having trouble deciding when to use each method.

]]> By: Rich Truncellito http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-194 Rich Truncellito Tue, 13 Mar 2012 13:30:09 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-194 I'm not sure that I understand the distinction of arbitrary shuffles of the data from i.i.d. sampling, when both are drawn from the same model/pool. I’m not sure that I understand the distinction of arbitrary shuffles of the data from i.i.d. sampling, when both are drawn from the same model/pool.

]]> By: Matt Bauman http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-193 Matt Bauman Tue, 13 Mar 2012 13:19:22 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-193 It seems to me that both these methods would suffer greatly with smaller sample sizes. Is there a rule of thumb that you follow to determine the minimum number of samples for performing the bootstrap? It seems to me that both these methods would suffer greatly with smaller sample sizes. Is there a rule of thumb that you follow to determine the minimum number of samples for performing the bootstrap?

]]> By: Rex Tien http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-192 Rex Tien Tue, 13 Mar 2012 06:30:19 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-192 It seems like resampling the data could amplify any sort of bias or error that was present. Is there a way of detecting this? Similarly, is there a way of detecting when the data are not sufficiently i.i.d. samples? Can you give an example of the case where the sampling is not i.i.d.? It seems like resampling the data could amplify any sort of bias or error that was present. Is there a way of detecting this?

Similarly, is there a way of detecting when the data are not sufficiently i.i.d. samples? Can you give an example of the case where the sampling is not i.i.d.?

]]> By: Ben Dichter http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-191 Ben Dichter Tue, 13 Mar 2012 04:53:04 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-191 I don't quite understand the point of the parametric bootstrap. In order to generate data we have to estimate the distribution parameters. Well if we are willing to accept those parameters, why do we even care about generating data? If we must choose a distribution to use MLE, then we could just look up the variance of that distribution in a book and skip the data generation step. Also, how are we to know how much we can trust our estimation of theta? I don’t quite understand the point of the parametric bootstrap. In order to generate data we have to estimate the distribution parameters. Well if we are willing to accept those parameters, why do we even care about generating data? If we must choose a distribution to use MLE, then we could just look up the variance of that distribution in a book and skip the data generation step. Also, how are we to know how much we can trust our estimation of theta?

]]> By: Matt Panico http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-190 Matt Panico Tue, 13 Mar 2012 04:12:51 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-190 It seems to me that the nonparametric bootstrap requires a very large sample set to allow the resampling to accurately represent the underlying CDF. Is there a good rule of thumb about sample size? It seems to me that the nonparametric bootstrap requires a very large sample set to allow the resampling to accurately represent the underlying CDF. Is there a good rule of thumb about sample size?

]]> By: Shubham Debnath http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-189 Shubham Debnath Tue, 13 Mar 2012 04:08:56 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-189 Because the parametric and nonparametric methods produce similar results and can be used for similar sets of data (albeit with a little manipulation), is there one used more often? Or perhaps preferred before trying the other one? Because the parametric and nonparametric methods produce similar results and can be used for similar sets of data (albeit with a little manipulation), is there one used more often? Or perhaps preferred before trying the other one?

]]> By: Sharlene Flesher http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-188 Sharlene Flesher Tue, 13 Mar 2012 03:46:56 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-188 Under what circumstances would you use bootstrap, rather than another method, to estimate SE? Under what circumstances would you use bootstrap, rather than another method, to estimate SE?

]]> By: Noah http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-187 Noah Tue, 13 Mar 2012 02:55:10 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-187 It seems that the nonparametric bootstrap will in most cases be easier and just as effective, are there any real benefits from using the parametric bootstrap? Also, it is mentioned that one of the shortcomings of the nonparametric bootstrap is that it requires an i.i.d. sample; however, I would have thought that this would also be a requirement for the parametric bootstrap? It seems that the nonparametric bootstrap will in most cases be easier and just as effective, are there any real benefits from using the parametric bootstrap? Also, it is mentioned that one of the shortcomings of the nonparametric bootstrap is that it requires an i.i.d. sample; however, I would have thought that this would also be a requirement for the parametric bootstrap?

]]> By: Rob Rasmussen http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-186 Rob Rasmussen Tue, 13 Mar 2012 01:47:08 +0000 http://www.stat.cmu.edu/~kass/smnp/?p=101#comment-186 I am confused as to how the estimator given in 9.21 would be more efficient than computing the sample mean. I am confused as to how the estimator given in 9.21 would be more efficient than computing the sample mean.

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