Re: [R] Limited number of principal components in PCA

Hi Billy, Thanks for posting your data. Okay, first off as Michael pointed out: > table(complete.cases(Q)) FALSE TRUE 1254 shows that of the 66 rows in your data set, only 54 of them are complete. That means when you use na = na.omit, you are actually only passing a data frame with 54

Re: [R] Limited number of principal components in PCA

At 19:07 04/08/2011, William Armstrong wrote: David and Josh, Thank you for the suggestions. I have attached a file ('q_values.txt') that contains the values of the 'Q' variable. David -- I am attempting an 'S' mode PCA, where the columns are actually the cases (different stream gaging station

Re: [R] Limited number of principal components in PCA

David and Josh, Thank you for the suggestions. I have attached a file ('q_values.txt') that contains the values of the 'Q' variable. David -- I am attempting an 'S' mode PCA, where the columns are actually the cases (different stream gaging stations) and the rows are the variables (the maximum f

Re: [R] Limited number of principal components in PCA

ited number of principal components in PCA Hi Billy, Can you provide your data? You could attach it as a text file or provide it by pasting the output of: dput(Q) into an email. It would help if we could reproduce what you are doing. You might also consider a list or forum that is more statis

Re: [R] Limited number of principal components in PCA

Hi Billy, Can you provide your data? You could attach it as a text file or provide it by pasting the output of: dput(Q) into an email. It would help if we could reproduce what you are doing. You might also consider a list or forum that is more statistics oriented than Rhelp, as your questions

[R] Limited number of principal components in PCA

Hi all, I am attempting to run PCA on a matrix (nrow=66, ncol=84) using 'prcomp' (stats package). My data (referred to as 'Q' in the code below) are separate river streamflow gaging stations (columns) and peak instantaneous discharge (rows). I am attempting to use PCA to identify regions of that