Shouldn't the "i" in your theta() function refer to the selected rows (a
"vector of indices" as referred to in the help file for boot) of the data
used by boot()?
theta <- function(data, i) {
data <- data[i, ]
data.cov <- cov(data)
data.eigen <- eigen(data.cov)
data.eigen$values[1]/sum(data.eigen$values)
}
Jean
r-help-boun...@r-project.org wrote on 08/12/2011 09:10:52 AM:
> [image removed]
>
> [R] Getting bootstrap statistic to work
>
> Alex Olssen
>
> to:
>
> r-help
>
> 08/12/2011 09:14 AM
>
> Sent by:
>
> r-help-boun...@r-project.org
>
> Hi R-help,
>
> I am trying to implement a nonparametric bootstrap to find the
> standard errors of a simple statistics - the ratio of two scalars. I
> am having difficulty getting boot() to work correctly. I code a
> function to create the ratio of the relevant scalars. theta(data, i).
> When I call the function for my data and every observation appearing
> once, theta(test, c(1)), I get the correct statistic for my original
> data. However when I use boot(test, theta, 200) the original
> statistic is incorrect.
>
> My code and data are below. The code is very short.
>
> Any help will be appreciated.
>
> Cheers,
> Alex
>
> library(boot)
> test <- read.csv("test.csv")
> test.mean <- mean(test)
> test.cov <- cov(test)*87/88 ## use the biased version as I am
> reproducing a result from a book
> test.eigen <- eigen(test.cov)
> theta <- function(data, i) {
> data <- data * i
> data.cov <- cov(data)
> data.eigen <- eigen(data.cov)
> data.eigen$values[1]/sum(data.eigen$values)
> }
> test.boot <- boot(test, theta, 200)
>
> test
> mec vec alg ana sta
> 1 77 82 67 67 81
> 2 63 78 80 70 81
> 3 75 73 71 66 81
> 4 55 72 63 70 68
> 5 63 63 65 70 63
> 6 53 61 72 64 73
> 7 51 67 65 65 68
> 8 59 70 68 62 56
> 9 62 60 58 62 70
> 10 64 72 60 62 45
> 11 52 64 60 63 54
> 12 55 67 59 62 44
> 13 50 50 64 55 63
> 14 65 63 58 56 37
> 15 31 55 60 57 73
> 16 60 64 56 54 40
> 17 44 69 53 53 53
> 18 42 69 61 55 45
> 19 62 46 61 57 45
> 20 31 49 62 63 62
> 21 44 61 52 62 46
> 22 49 41 61 49 64
> 23 12 58 61 63 67
> 24 49 53 49 62 47
> 25 54 49 56 47 53
> 26 54 53 46 59 44
> 27 44 56 55 61 36
> 28 18 44 50 57 81
> 29 46 52 65 50 35
> 30 32 45 49 57 64
> 31 30 69 50 52 45
> 32 46 49 53 59 37
> 33 40 27 54 61 61
> 34 31 42 48 54 68
> 35 36 59 51 45 51
> 36 56 40 56 54 35
> 37 46 56 57 49 32
> 38 45 42 55 56 40
> 39 42 60 54 49 33
> 40 40 63 53 54 25
> 41 23 55 59 53 44
> 42 48 48 49 51 37
> 43 41 63 49 46 34
> 44 46 52 53 41 40
> 45 46 61 46 38 41
> 46 40 57 51 52 31
> 47 49 49 45 48 39
> 48 22 58 53 56 41
> 49 35 60 47 54 33
> 50 48 56 49 42 32
> 51 31 57 50 54 34
> 52 17 53 57 43 51
> 53 49 57 47 39 26
> 54 59 50 47 15 46
> 55 37 56 49 28 45
> 56 40 43 48 21 61
> 57 35 35 41 51 50
> 58 38 44 54 47 24
> 59 43 43 38 34 49
> 60 39 46 46 32 43
> 61 62 44 36 22 42
> 62 48 38 41 44 33
> 63 34 42 50 47 29
> 64 18 51 40 56 30
> 65 35 36 46 48 29
> 66 59 53 37 22 19
> 67 41 41 43 30 33
> 68 31 52 37 27 40
> 69 17 51 52 35 31
> 70 34 30 50 47 36
> 71 46 40 47 29 17
> 72 10 46 36 47 39
> 73 46 37 45 15 30
> 74 30 34 43 46 18
> 75 13 51 50 25 31
> 76 49 50 38 23 9
> 77 18 32 31 45 40
> 78 8 42 48 26 40
> 79 23 38 36 48 15
> 80 30 24 43 33 25
> 81 3 9 51 47 40
> 82 7 51 43 17 22
> 83 15 40 43 23 18
> 84 15 38 39 28 17
> 85 5 30 44 36 18
> 86 12 30 32 35 21
> 87 5 26 15 20 20
> 88 0 40 21 9 14
>
> ______________________________________________
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