Good Morning:
I've read many, many posts on the r-help system and I feel compelled to quickly
admit that I am relatively new to R, I do have several reference books around
me, but I cannot count myself among the fortunate who seem to strong
programming intuition.
I have a data set consisting of 1637 observations of five variables: tensile
strength, yield strength, elongation, hardness and a character indicator with
three levels: (Y)es, (N)o, and (F)ail.
My objective is to randomly sample various subsets from this data set and then
evaluate these subsets using simple parameters among them tests for normality,
shape and skewness. The data set is ordered by the character variable prior to
sampling, and the samples are weighted to mirror representation in an overall,
physical process.
I am sampling the data set using this code:
sample <- dataset[sample(1:1637, 500,
prob=c(rep(163.7/1637,513),rep(245.5/1637,197),rep(1227.8/1637,927)),replace =
TRUE),]
What I would like to do is iterate this process to create many (say 500 or
more) sampled sets of n=500 and then evaluate each set for the parameters of
interest. I would actually be evaluating each variable within each subset for
my characteristic of interest. I am familiar with sampling and saving single
columns of data to do this sort of thing, but I am not sure how to accomplish
this with a multiple-variable data set.
For example, I am currently iterating this using a clunky process:
mysamples<-list()
for (i in 1:10){
mysamples[[i]] <- dataset[
sample(1:1637,100,prob=c(rep(163.7/1637,513),rep(245.5/1637,197),rep(1227.8/1637,927)),replace
= TRUE), ]
}
But this leaves me with the additional task of defining each mysample[i]
iteration and converting it to a form on which I can apply a standard
statistical test like mean() or skewness() to the variable columns within each
subset. I have attempted to iteratively convert these lists using this code:
mat<-matrix(nrow=100,ncol=5)
for (i in 1:length(mysamples))
{mat[i]<-do.call('rbind',mysamples[i])}
but running the code generates the error message: number of items to replace is
not a multiple of replacement length. I have tried unsuccessfully, by reading
many, many helpful r-help emails on this error, to understand my probably
obvious mistake.
Based on the small amount that I think I know about R it seems to me that
sampling the data frame and containing the samples in a list is likely a pretty
inefficient way to do this task. Any help that any of you could provide to
assist me in iteratively sampling the data frame, and storing the samples in a
form on which I can apply other statistical tests would be greatly appreciated.
Thank you very much for taking the time to consider my questions.
Adam
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