# [R] Arguments in functions

Phil Spector spector at stat.berkeley.edu
Thu Dec 16 21:50:33 CET 2010

Paul -
Please take a look at the help file for boot, i.e. type

?boot

at the R prompt.  There you will see, along with other
information:

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.

Since the default for sim is "ordinary", the boot function will automatically
pass the entire data set as the first argument, and the indices of the bootstrap
sample as the second argument.

Hope this helps.
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spector at stat.berkeley.edu

On Thu, 16 Dec 2010, Prew, Paul wrote:

>
> Hello,  I'm not much of a programmer, and am trying to understand the workings of the function below called "RStatFctn" within this bootstrap procedure.
>
> RStatFctn is defined to have two arguments: "x", intended to be a data vector; and "d" intended to be an index (or so it looks to me).
> Later, "rnormdat" is created to be the data vector.   However, when RStatFctn is called within the bootstrap function, I don't see where "rnormdat" is explicitly passed to RStatFctn as the data vector "x".  And I don't see where any values are ever passed to the index variable "d", or where any index is ever referenced or used in conjunction with RStatFctn.
>
>
> Thanks, Paul
>
> library(boot)
>
> RStatFctn <- function(x,d) {return(mean(x[d]))}
>
> b.basic = matrix(data=NA, nrow=1000, ncol=2) b.normal = matrix(data=NA, nrow=1000, ncol=2) b.percent =matrix(data=NA, nrow=1000, ncol=2) b.bca =matrix(data=NA, nrow=1000, ncol=2)
>
> for(i in 1:1000){
> rnormdat = rnorm(30,0,1)
> b <- boot(rnormdat, RStatFctn, R = 1000) b.ci=boot.ci(b, conf =0.95,type=c("basic","norm","perc","bca"))
> b.basic[i,] = b.ci\$basic[,4:5]
> b.normal[i,] = b.ci\$normal[,2:3]
> b.percent[i,] = b.ci\$percent[,4:5]
> b.bca[i,] = b.ci\$bca[,4:5]
> }
>
> Paul Prew   ▪  Statistician
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