This thread strikes me as pretty far off-topic for a forum dedicated to
software support on R.
https://www.r-project.org/mail.html#instructions
"The ‘main’ R mailing list, for discussion about problems and solutions
using R, announcements (not covered by ‘R-announce’ or ‘R-packages’,
see above), a
To check whether the data are being read in appropriately, what happens
when you plot the distribution of each of the independent variables on
the respective systems?
-A
On Wed, 5 Jun 2019 12:32:28 +0200
Olivier Crouzet wrote:
> Hi,
>
> 32bit vs. 64bit systems?
>
> Another thing I would look
Hi all,
Following some updates to R that I received via Synaptic Package
Manager on Ubuntu 16.04 (looks like I now have R 3.4.4-1xenial0), I
have been unable to reinstall rgdal, and I need help.
Initially I was getting error messages about dependencies on GDAL
1.11.4, but after following instruct
I'm trying to develop a linear model for crop productivity based on
variables published as part of the SSURGO database released by the
USDA. My default is to just run lm() with continuous predictor
variables as numeric, and discrete predictor variables as factors, but
some of the discrete variable
rfect for making
comparisons!
Thanks again to everybody who's tried to help me out on this!
Alexandra
On Thu, 2011-06-23 at 21:29 +0200, Jan van der Laan wrote:
> Alexandra,
>
> Have a look at add1 and drop1.
>
> Regards,
> Jan
>
>
> On 06/23/2011 07:32 PM, Ale
Here's a more general question following up on the specific question I
asked earlier:
Can anybody recommend an R command other than mle.aic() (from the wle
package) that will give back a ranked list of submodels? It seems like
a pretty basic piece of functionality, but the closest I've been able
On Thu, 2011-06-23 at 09:29 -0400, Alexandra Thorn wrote:
> Ok, here's some example code showing how I get different output for
AIC
> vs. mle.aic(). Now that I've taken another look at the independent
> variables, I'm wondering whether missing values in one of the
vari
01 1 1 1 -57.34
[20,] 01 1 1 0 -56.35
Printed the first 20 best models
R> AIC(lm(y1~xA)) # Model 1 above
[1] -120.3801
R> AIC(lm(y1~xA+x15)) # Model 2 above
[1] -110.8642
R> AIC(lm(y1~xA+x5)) # Model 3 above
[1] -118.9906
On Thu, 2011-06-23 at 09:0
>
>
> Dr. Rubén Roa-Ureta
> AZTI - Tecnalia / Marine Research Unit
> Txatxarramendi Ugartea z/g
> 48395 Sukarrieta (Bizkaia)
> SPAIN
>
>
>
> > -Mensaje original-
> > De: r-help-boun...@r-project.org
> > [mailto:r-h
I know this a newbie question, but I've only just started using AIC for
model comparison and after a bunch of different keyword searches I've
failed to find a page laying out what the differences are between the
AIC scores assigned by AIC() and mle.aic() using default settings.
I started by usin
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