[R] scoping problem

[Prof Brian Ripley]

Local updating is what I would have recommended.

But predict() will work correctly with NA values in the fit if the latter 
was done with na.action=na.exclude.  I would find it clearer to use 
fitted() here, which also works for na.action=na.exclude.

On Wed, 24 Oct 2007, Christos Hatzis wrote:

> Another way to do this without messing with environments is to update the
> data and formula locally within the function and re-run the regression on
> the updated model/data:
>
> tukey.test <- function(m) {
>    ud <- data.frame( m$model, pred2=m$fitted.values^2 )
>    uf <- update.formula(formula(m$terms), ~ . + pred2)
>    summary(lm(uf, ud))$coef
> }
>
>> data(BOD)
>> m1 <- lm(demand~Time,BOD)
>> tukey.test(m1)
>              Estimate Std. Error    t value  Pr(>|t|)
> (Intercept) 12.5854086  5.0344850  2.4998403 0.0877190
> Time         7.5390634  6.1271204  1.2304415 0.3062126
> pred2       -0.1096744  0.1148654 -0.9548081 0.4101142
>
>
>> -----Original Message-----
>> From: r-help-bounces at r-project.org
>> [mailto:r-help-bounces at r-project.org] On Behalf Of Sandy Weisberg
>> Sent: Wednesday, October 24, 2007 3:44 PM
>> To: r-help at stat.math.ethz.ch
>> Subject: [R] scoping problem
>>
>> I would like to write a function that computes Tukey's 1 df
>> for nonadditivity.  Here is a simplified version of the
>> function I'd like to
>> write:  (m is an object created by lm):
>>
>> tukey.test <- function(m) {
>>   m1 <- update(m, ~.+I(predict(m)^2))
>>   summary(m1)$coef
>>   }
>>
>> The t-test for the added variable is Tukey's test.  This won't work:
>>
>> data(BOD)
>> m1 <- lm(demand~Time,BOD)
>> tukey.test(m1)
>>
>> Error in predict(m) : object "m" not found
>>
>> This function doesn't work for two reasons:
>> 	1. The statement m1 <- update(m, ~.+I(predict(m)^2))
>> can't see 'm' in the call to predict.
>> 	2. If in creating m missing values had been present,
>> then predict(m), even if it could be computed, could be of
>> the wrong length.
>>
>> Can anyone help?
>>
>>
>>
>> --
>> Sanford Weisberg, sandy at stat.umn.edu
>> Office and mailing address:
>> University of Minnesota, School of Statistics
>> 312 Ford Hall, 224 Church St. SE, Minneapolis, MN  55455
>> 612-625-8355, FAX 612-624-8868
>>
>> St. Paul office:
>> 146 Classroom-Office Building, 612-625-8777
>>
>> ______________________________________________
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>> PLEASE do read the posting guide
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595