[R] problem with gls finding model terms without specifying data=named.object
Paul.Rustomji at csiro.au
Paul.Rustomji at csiro.au
Mon Feb 16 11:41:11 CET 2009
Hello R-help
I am having trouble getting gls to find the R objects that comprise a linear model when the data=named.object option(option!) is not specified. In the gls() help it states data is "an optional data frame containing the variables named in model, correlation, weights, and subset. By default the variables are taken from the environment from which gls is called".
An example:
> temp <- data.frame(x=1:10,y=11:20+rnorm(10))
> temp
x y
1 1 11.52458
2 2 10.77643
3 3 12.56845
4 4 14.48822
5 5 13.58116
6 6 16.26223
7 7 17.89619
8 8 19.40359
9 9 18.56699
10 10 21.05374
> gls(temp$y~temp$x)
Error in eval(expr, envir, enclos) : object "y" not found
> gls(y~x,data=temp)
Generalized least squares fit by REML
Model: y ~ x
Data: temp
Log-restricted-likelihood: -14.00387
Coefficients:
(Intercept) x
9.366256 1.135619
Degrees of freedom: 10 total; 8 residual
Residual standard error: 0.9156084
I'm trying hard to avoid having to specify the data option if at all possible.
Paul
-------------------------------
R version 2.8.0 (2008-10-20) (yes I know its not 2.8.1 but nothing in the 2.8.1 news seemed to be relevant, I also tried on a different PC with R 2.7.0 but same problem)
i386-pc-mingw32
locale:
LC_COLLATE=English_Australia.1252;LC_CTYPE=English_Australia.1252;LC_MONETARY=English_Australia.1252;LC_NUMERIC=C;LC_TIME=English_Australia.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] nlme_3.1-89
loaded via a namespace (and not attached):
[1] grid_2.8.0 lattice_0.17-17
-----------------------------------------------
Information on package 'nlme'
Description:
Package: nlme
Version: 3.1-89
Date: 2008-06-07
Priority: recommended
Title: Linear and Nonlinear Mixed Effects Models
Author: Jose Pinheiro <Jose.Pinheiro at pharma.novartis.com>, Douglas Bates <bates at stat.wisc.edu>,
Saikat DebRoy <saikat at stat.wisc.edu>, Deepayan Sarkar <Deepayan.Sarkar at R-project.org>,
the R Core team.
Maintainer: R-core <R-core at R-project.org>
Description: Fit and compare Gaussian linear and nonlinear mixed-effects models.
Paul Rustomji
Rivers and Estuaries
CSIRO Land and Water
GPO Box 1666
Canberra ACT 2601
ph +61 2 6246 5810
mobile 0406 375 739
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