A set of curlies should help.
As in
> replicate(5, {y <- runif(20); mean(y)})
[1] 0.4926800 0.5356511 0.5343938 0.5313422 0.5287927
-pd
BTW: sum(replicate(10000,...))/10000 is simpler and less error-prone written as
mean(replicate(10000,....))
> On 09 Oct 2015, at 01:37 , Curtis Browne <curtis_brown...@hotmail.com> wrote:
>
> I would like to essentially do a randomization p-test (10,000 replications in
> this case) to check how often I would see a linear correlation in my data as
> strong or stronger than I did with the original data (with a correlation
> value of 0.9796619). The code which I thought would work is below:
>
> sum(replicate(10000,data$Scram <- sample(data$Changeinmass,10, replace =
> FALSE); with(data,cor(Current,data$Scram))>=0.9796619))/10000
>
> With the error:
>
> Error: unexpected ';' in "sum(replicate(10000,data$Scram <-
> sample(data$Changeinmass,10, replace = FALSE);"
>
> Is there any method of replicating both the function of assigning a random
> sample of the data to a column, and the function of then performing a Pearson
> correlation test between data$Current and data$Scram?
>
> [[alternative HTML version deleted]]
>
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--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk Priv: pda...@gmail.com
______________________________________________
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