[R] dr ()

2005-04-22 Thread Jessica Higgs
Hi all--
A quick question about the dr () function. I am using this function to 
reduce the dimensions of a data set I have that involves 14 predictor 
variables and one predictant or response. The goal is to discover which 
variables play the most important role in determining the response and, 
thus, to reduce the variables. I would like to use the sliced inverse 
regression method (SIR) within this function but each time I specify 8 
slices, it only performs 5 slices. Any suggestions/thoughts?

THanks,
Jessica
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[R] searching through a matrix

2005-02-27 Thread Jessica Higgs
I am trying to search through a matrix I have (x) to see if there are any 
missing values. This is what I have been using:

for (i in 1:3455)
   for (j in 1:24)
   if (is.na(x[i,j])) break;
i
j
When I run the program, it either freezes or stops and returns the last 
entry in the matrix (x[3455,24]). I need to figure out what values in my 
data matrix are missing because I am using prcomp and it keeps giving me an 
error starting that there are missing or infinite values in  x. My data 
matrix does have some values that are equal to zero but zero doesn't mean 
that the data is missing. it just indicates that that value is equivalent 
to zero. Any suggestions for how to fix this problem?

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[R] eigen vector question

2005-02-17 Thread Jessica Higgs
Sorry to bother everyone, but I've looked in all of the help files and 
manuals I have and I can't find the answer to this question.  I'm doing 
principle component analysis by calculating the eigen vectors of a 
correlation matrix that I have that is composed of 21 parameters.  I have 
the eigen vectors and their values that R produced for me but I'm not sure 
how to tell which eigen vector/value corresponds to which parameter because 
when R produces eigen vectors it does so in decreasing order of 
significance, meaning that the eigen vector that explains the most of the 
variance is listed first, followed by the next eigen vector, etc etc. Any 
help would be appreciated. Feel free to write back if you need more 
information on my problem.  Thanks!

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Re: [R] Creating a correlation Matrix

2005-02-07 Thread Jessica Higgs
I've tried using cor() by the following sequence:
C <- cor(x, y = NULL, use = "all.obs", method = c("pearson"))
where x is my matrix of 21 columns and 3471 rows.
and I get this error:
Error in cor(x, y = NULL, use = "all.obs", method = c("pearson")) :
missing observations in cov/cor
any suggestions?
At 08:32 AM 2/7/2005 -0800, Spencer Graves wrote:
 Have you considered "cor"?  The command 'help.search("correlation")' 
suggests among other functions "var(stats)", the documentation for which 
also includes "cor".
 If this is not adequate, "PLEASE do read the posting guide! 
http://www.R-project.org/posting-guide.html ".  It may help you get more 
useful replies in the future.  spencer graves

Jessica Higgs wrote:
Hi all:
I have a question on how to go about creating a correlation matrix.  I 
have a huge amount of data21 variables for 3471 times. I want to see 
how each of the variables correlate to each other.  Any help would be 
appreciated, including which package and which functions I should use to 
do this.

Thanks,
Jessica Higgs
Masters Student
Department of Meteorology
Penn State University
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[R] Creating a correlation Matrix

2005-02-07 Thread Jessica Higgs
Hi all:
I have a question on how to go about creating a correlation matrix.  I have 
a huge amount of data21 variables for 3471 times. I want to see how 
each of the variables correlate to each other.  Any help would be 
appreciated, including which package and which functions I should use to do 
this.

Thanks,
Jessica Higgs
Masters Student
Department of Meteorology
Penn State University
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[R] using RODBC

2005-01-28 Thread Jessica Higgs
I am trying to bring data into R from an excel spreadsheet in order to 
perform several statistical tests on it.  I was trying to use 
odbcConnectExcel in the RODBC package.  Once I am connected to the excel 
file, how do I select rows and columns from the file in order to analysis 
them in R.

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