On Nov 19, 2014, at 6:08 AM, i.petzev wrote:
> Hi David,
>
> thanks a lot for the response. I see that this works. I am not sure, however,
> what the appropriate way to do this is. It also works if you do not define
> weights in the boot() function (weighted bootstrap) but rather in the
> vw_m_diff function (ordinary bootstrap), i.e.,
>
>
> vw_m_diff <- function(dataset,d) {
> differences <- dataset[d,1]-dataset[d,2]
> weights <- dataset[d, "weights"]
> return(weighted.mean(x=differences, w=weights))
> }
>
> with
>
> boot(dataset, statistic=vw_m_diff, R = 1000)
I don't undertand how that is in the slightest way different than what I
suggested. You've only substituted 'd' for 'w' as a formal parameter in the
function. That should not change the processed results at all.
--
David.
>
> I guess this is rather a statistical question and hence I will have to look
> further into it.
>
> In any case, thanks a lot for your help.
>
> Best
>
>
>
> On 15 Nov 2014, at 17:27, David Winsemius <dwinsem...@comcast.net> wrote:
>
>>
>> On Nov 14, 2014, at 3:18 PM, David Winsemius wrote:
>>
>>>
>>> On Nov 14, 2014, at 12:15 PM, ivan wrote:
>>>
>>>> Hi,
>>>>
>>>> I am trying to compute bootstrap confidence intervals for weighted means of
>>>> paired differences with the boot package. Unfortunately, the weighted mean
>>>> estimate lies out of the confidence bounds and hence I am obviously doing
>>>> something wrong.
>>>>
>>>> Appreciate any help. Thanks. Here is a reproducible example:
>>>>
>>>>
>>>> library(boot)
>>>> set.seed(1111)
>>>> x <- rnorm(50)
>>>> y <- rnorm(50)
>>>> weights <- runif(50)
>>>> weights <- weights / sum(weights)
>>>> dataset <- cbind(x,y,weights)
>>>> vw_m_diff <- function(dataset,w, d) {
>>>
>>> My understanding of the principle underlying the design of the bootstrapped
>>> function was that the data was the first argument and the index vector was
>>> the second. (I admit to not knowing what it would do with a third argument.
>>> So I would have guessed that you wanted:
>>>
>>> vw_m_diff <- function(dataset,w) {
>>> differences <- dataset[d,1]-dataset[d,2]
>>> weights <- dataset[w, "weights"]
>>> return(weighted.mean(x=differences, w=weights))
>>> }
>>
>> I'm sorry. That was the code I first editted. This is the code that produced
>> that output:
>>
>> vw_m_diff <- function(dataset,w) {
>> differences <- dataset[w,1]-dataset[w,2]
>> weights <- dataset[w, "weights"]
>> return(weighted.mean(x=differences, w=weights))
>> }
>>
>>>
>>> I get what appears to me as a sensible set of estimates (since they seem
>>> centered on zero) although I further admit I do not know what the theoretic
>>> CI _should_ be for this problem:
>>>
>>>> res_boot <- boot(dataset, statistic=vw_m_diff, R = 1000, w=dataset[,3])
>>>> boot.ci(res_boot)
>>> BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS
>>> Based on 1000 bootstrap replicates
>>>
>>> CALL :
>>> boot.ci(boot.out = res_boot)
>>>
>>> Intervals :
>>> Level Normal Basic
>>> 95% (-0.5657, 0.4962 ) (-0.5713, 0.5062 )
>>>
>>> Level Percentile BCa
>>> 95% (-0.6527, 0.4249 ) (-0.5579, 0.5023 )
>>> Calculations and Intervals on Original Scale
>>>
>>>
>>>> differences <- dataset[d,1]-dataset[d,2]
>>>> weights <- w[d]
>>>> return(weighted.mean(x=differences, w=weights))
>>>> }
>>>> res_boot <- boot(dataset, statistic=vw_m_diff, R = 1000, w=dataset[,3])
>>>> boot.ci(res_boot)
>>>>
>>>> *BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS*
>>>> *Based on 1000 bootstrap replicates*
>>>>
>>>> *CALL : *
>>>> *boot.ci <http://boot.ci>(boot.out = res_boot)*
>>>>
>>>> *Intervals : *
>>>> *Level Normal Basic *
>>>> *95% (-0.8365, -0.3463 ) (-0.8311, -0.3441 ) *
>>>>
>>>> *Level Percentile BCa *
>>>> *95% (-0.3276, 0.1594 ) (-0.4781, -0.3477 ) *
>>>>
>>>> weighted.mean(x=dataset[,1]-dataset[,2], w=dataset[,3])
>>>>
>>>> *[1] -0.07321734*
>>>>
>>>> [[alternative HTML version deleted]]
>>>>
>>>> ______________________________________________
>>>> R-help@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.
>>>
>>> David Winsemius
>>> Alameda, CA, USA
>>>
>>> ______________________________________________
>>> R-help@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.
>>
>> David Winsemius
>> Alameda, CA, USA
>
David Winsemius
Alameda, CA, USA
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