From pdalgd at gmail.com  Mon Jun  6 21:15:25 2011
From: pdalgd at gmail.com (peter dalgaard)
Date: Mon, 6 Jun 2011 21:15:25 +0200
Subject: [Rd] Possible bug in termplot function (stats package) ?
In-Reply-To: <BANLkTi=uHfZ62TSfLa-a+E-n9RU47_vS5A@mail.gmail.com>
References: <BANLkTikkDxdR_1+TJNX5LMkr23spvOJ4+A@mail.gmail.com>
	<9B2E15B5-AE4F-4849-96D5-A5DE8896DC80@gmail.com>
	<BANLkTi=uHfZ62TSfLa-a+E-n9RU47_vS5A@mail.gmail.com>
Message-ID: <94E402C0-10C7-4770-9AB0-B1E33A1779E1@gmail.com>


On Jun 6, 2011, at 20:38 , Joris Meys wrote:

> On Mon, Jun 6, 2011 at 6:29 PM, peter dalgaard <pdalgd at gmail.com> wrote:
>> 
>> On Jun 6, 2011, at 17:15 , Joris Meys wrote:
>> 
> **snip**
>>> If nothing is found, an error is returned. If
>>> anything is found, data won't be NULL, so line 20, when reached, will
>>> always return FALSE. Can it be that lines 18 and 19 should be removed
>>> from the function?
>> 
>> 
>> I think this is a false assumption. What keeps model$call$data from being NULL?
>> 
> Apart from a dataframe that is explicitly assigned NULL, I can't
> imagine a case where model$call$data would be NULL. If it's not found,
> the statement returns an error. If it is found and it is NULL, your
> model call will have thrown an error earlier, so you won't even have
> an object to plot. If you can give me one example where that code
> actually makes sense, I'll be very happy. But right now, it doesn't
> make any sense at all to me.

I'd say that the burden of proof is really on your side, but how hard can it be:

> x <- 1:10
> y <- rnorm(10)
> m <- lm(y~x)
> m$call
lm(formula = y ~ x)
> m$call$data
NULL


-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com



[Rd] Possible bug in termplot function (stats package) ?
peter dalgaard