I am relatively new to R, but very pleased with what I can do with it so
far.
I am embarrassed to ask what seems like a simple question but I am at my
wits end. Basically I have written a function to calculate a bootstrapped
statistic on a list of values. The function works perfectly if I can feed it
the right data. I am exporting data into R as a dataframe and then assigning
each column to the list and running the function use a for loop. The problem
is what is the best way to convert the columns to a list. The column names
and the number of columns will vary depending on the dataset. I am currently
converting the dataframe to a matrix and the assigning each column of the
matrix to the list in turn:
#InputData is the dataframe
RunTests <- function (InputData)
{
n <- length(InputData)
Chem <- colnames(InputData)
for (i in 1:n){
print (Chem[i])
Data <- data.matrix(InputData)
x <- Data[,n]
na.omit(x)
#print(x)
UCL <- HallBoot(x)
print (UCL)
}
}
Although this works some of the time, missing values are not removed. This
is a huge problem as the number of observation is each column is quite
variable. Obviously the na.omit is not working the way I expect. Any help
would be appreciated, including a whole new approach to sending the data to
the HallBoot function.
Michael J. Bock, PhD.
ARCADIS
24 Preble St. Suite 100
Portland, ME 04101
207.828.0046
fax 207.828.0062
______________________________________________
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
