You are using the boot function incorrectly. This is taken from the
help page:
statistic: A function which when applied to data returns a vector
containing the statistic(s) of interest. When
`sim="parametric"', the first argument to
`statistic' must be
the data. For each replicate a simulated dataset returned by
`ran.gen' will be passed. In all other cases `statistic'
must take at least two arguments. The first argument passed
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
will always be the original data. The second will be a vector
of indices, frequencies or weights which define the bootstrap
sample.
The default is nonparametric bootstrap (sim = "ordinary"), so you need
to specify a function with TWO arguments. Try
x <- rnorm(100)
boot(x, function(x, i) mean(x[i]), R = 1000)$t
-roger
Erin Hodgess wrote:> Dear r People
>
>
> I have a bootstrap question, please.
>
> (this may possibly be a problem with my understanding of the bootstrap)
>
> Suppose I have a sample of size 15, x[1], ...x[15].
>
> This is a sample which is small compared to the population.
>
> by the way, the x[i] are iid and have a common distribution F.
>
> As I understand the bootstrap, that function will take a user specified
> number of repititions. In each repitition, each element x[i] has an
> equal chance of selection.
>
> Suppose I want to estimate the mean.
>
> In each rep, a new sample is generated. the mean is calculated in each
rep.
>
>
> I would like to see those means.
>
> If I use the boot command,
>
> boot(x,mean,R=40)$t
>
> I thought that I would obtain 40 different values. However, those $t
values
> are all the same.
>
> what am I doing wrong, please?
>
> thanks yet again!
>
> sincerely,
> Erin Hodgess
> mailto: hodgess at uhddx01.dt.uh.edu
>
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>