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
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
