Displaying 5 results from an estimated 5 matches for "utmb".
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utm
2003 Dec 31
2
how to use apply on a two variable t-test
...data[i,5:9])
doesn't print anything! it processes for awhile, so i know it's doing
the calculations.
t.test(data[1,1:4],data[1,5:9])
works fine! prints to the screen as i'd expect.
i have checked and double checked that sink() is empty. please also
send your reply to jbdunsmo at utmb.edu. i receive the digest version of
the mailing list.
thanks for any help,
jason
2005 Feb 04
5
simple example of C interface to R
i'd like to use the C interface to R in a program i'm writing. as a
starting point, i'm trying to create a very simple C program that uses
R. i've read the R documentation on this, but i'm having trouble
figuring out where SEXP is defined and how to use it.
i noticed someone else on this list also tried to use the C interface,
but they ran into similar problems:
2009 Jan 17
2
plot data with a colour scale - more details!
Hello again,
I am trying to create a color scale plotting the hydroathy index (y-axis) versus residue (x-axis) - each residue (1-100) has a value between 0-1. I've been trying to create a scale where:
0-0.499: increasing intensity of red
0.5- yellow
0.51 - 1 increasing intensity of green.
THis is in lieu of a line graph.
I'm not sure which type of plot to begin with - I attempted to
2011 Jan 25
2
FW: question about the pt() calculation
From: Leitch, Matthew C.
Sent: Monday, January 24, 2011 6:53 PM
To: 'info at network-theory.co.uk'
Subject: question about the pt() calculation
Hello
Thank you for your time. I am a graduate student at the University of Texas Medical Branch, and I was wondering if you could help me with a R program I am writing. I have some data that is stored a file that has 1733 rows and 4 columns.
2011 May 03
1
Unexp. behavior from boot with multiple statistics
I am attempting to use package boot to summarize and compare the performance
of three models. I'm using R 2.13.0 in a Win32 environment.
My statistic function returns a vector of 6 values, 3 of which are error
rates for different models, and 3 are pairwise differences between those
error rates. It looks like:
multiEst<-function(dat,i)
{
....
c(E1,E2,E3,E2-E1,E3-E1,E3-E2);
}