On Nov 9, 2009, at 12:30 PM, Dobrozemsky Georg wrote:
Hi!
When checking validity of a model for a large number
of experimental data I thought it to be interesting
to check the information provided by
the summary method programmatically.
Still I could not find out which method to
use to get to those data.
Example (not my real world data, but to show the point):
[BEGIN]
DNase1 - subset(DNase, Run == 1)
fm1DNase1 - nls(density ~ SSlogis(log(conc), Asym, xmid, scal),
DNase1)
summary(fm1DNase1)
Formula: density ~ SSlogis(log(conc), Asym, xmid, scal)
Parameters:
Estimate Std. Error t value Pr(|t|)
Asym 2.345180.07815 30.01 2.17e-13 ***
xmid 1.483090.08135 18.23 1.22e-10 ***
scal 1.041460.03227 32.27 8.51e-14 ***
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 0.01919 on 13 degrees of freedom
Number of iterations to convergence: 0
Achieved convergence tolerance: 3.302e-06
[END]
now i would like something like
property(fm1DNase1,'Asym','StErr')
[1] 0.07815
property(fm1DNase1,'xmid','Pr')
[1] 1.22e-10
Applying str to the summary object should have given you sufficient
clues. Then it is a simple matter of extracting the right component,
and then properly extracting from the matrix with the correct names:
str(summary(fm1DNase1)$parameters)
num [1:3, 1:4] 2.3452 1.4831 1.0415 0.0782 0.0814 ...
- attr(*, dimnames)=List of 2
..$ : chr [1:3] Asym xmid scal
..$ : chr [1:4] Estimate Std. Error t value Pr(|t|)
summary(fm1DNase1)$parameters['Asym',Std. Error]
[1] 0.07815395
summary(fm1DNase1)$parameters['xmid',Pr(|t|)]
[1] 1.218535e-10
I hope you understand the point (and yes,
I read manuals, tried help(), read through
the archives), sorry if still this is trivial :P
wfG
George
+---
| Dr. Georg Dobrozemsky
| Dept. of. Nuclear Medicine
| Med. Univ. Vienna
+---
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