[Rd] Apparent bug in behavior of formulas with '-' operator for lm
Joris Meys
jorismeys at gmail.com
Fri Mar 16 13:22:45 CET 2018
Technically it is used as a predictor in the model. The information is
contained in terms :
> terms(x ~ . - z, data = d)
x ~ (y + z) - z
attr(,"variables")
list(x, y, z)
attr(,"factors")
y
x 0
y 1
z 0
attr(,"term.labels")
[1] "y"
attr(,"order")
[1] 1
attr(,"intercept")
[1] 1
attr(,"response")
[1] 1
attr(,".Environment")
And the model.frame contains it :
> head(model.frame(x ~ . - z, data = d))
x y z
2 -0.06022984 -0.4483109 b
3 1.25293390 0.2687065 c
4 -1.11811090 0.8016076 d
5 -0.75521720 -0.7484931 e
6 0.93037156 0.4128456 f
7 1.32052028 -1.6609043 a
It is at the construction of the model.matrix that z disappears, but the
contrasts information for z is still attached :
> attr(model.matrix(x ~ . - z, data = d),"contrasts")
$z
[1] "contr.treatment"
As you can see from the error you printed, it is model.frame() complaining
about it. In this case it wouldn't be necessary, but it is documented
behaviour of model.frame. Which is why I didn't say "this is not a bug",
but "this is not a bug per se". Meaning that this is not optimal behaviour
and might not what you expect, but it follows the documentation of the
underlying functions.
Solving it would require a bypass of model.frame() to construct the correct
model,matrix for the new predictions, and that's far from trivial as
model.matrix() itself depends on model.frame().
Cheers
Joris
On Fri, Mar 16, 2018 at 1:09 PM, Mark van der Loo <mark.vanderloo at gmail.com>
wrote:
> Joris, the point is that 'z' is NOT used as a predictor in the model.
> Therefore it should not affect predictions. Also, I find it suspicious that
> the error only occurs when the response variable conitains missings and 'z'
> is unique (I have tested several other cases to confirm this).
>
> -Mark
>
> Op vr 16 mrt. 2018 om 13:03 schreef Joris Meys <jorismeys at gmail.com>:
>
>> It's not a bug per se. It's the effect of removing all observations
>> linked to a certain level in your data frame. So the output of lm() doesn't
>> contain a coefficient for level a of z, but your new data contains that
>> level a. With a small addition, this works again:
>>
>> d <- data.frame(x=rnorm(12),y=rnorm(12),z=rep(letters[1:6],2))
>>
>> d$x[1] <- NA
>> m <- lm(x ~ . -z, data=d)
>> p <- predict(m, newdata=d)
>>
>> This is linked to another discussion earlier on stackoverflow :
>> https://stackoverflow.com/questions/48461980/prediction-in-r-glmm
>> which lead to an update to lme4 : https://github.com/lme4/lme4/issues/452
>>
>> The point being that factors in your newdata should have the same levels
>> as factors in the original data that was used to fit the model. If you add
>> levels to these factors, it's impossible to use that model to predict for
>> these new data.
>>
>> Cheers
>> Joris
>>
>> On Fri, Mar 16, 2018 at 10:21 AM, Mark van der Loo <
>> mark.vanderloo at gmail.com> wrote:
>>
>>> Dear R-developers,
>>>
>>> In the 'lm' documentation, the '-' operator is only specified to be used
>>> with -1 (to remove the intercept from the model).
>>>
>>> However, the documentation also refers to the 'formula' help file, which
>>> indicates that it is possible to subtract any term. Indeed, the following
>>> works with no problems (the period '.' stands for 'all terms except the
>>> lhs'):
>>>
>>> d <- data.frame(x=rnorm(6), y=rnorm(6), z=letters[1:2])
>>> m <- lm(x ~ . -z, data=d)
>>> p <- predict(m,newdata=d)
>>>
>>> Now, if I change 'z' so that it has only unique values, and I introduce
>>> an
>>> NA in the predicted variable, the following happens:
>>>
>>> d <- data.frame(x=rnorm(6),y=rnorm(6),z=letters[1:6])
>>> d$x[1] <- NA
>>> m <- lm(x ~ . -z, data=d)
>>> p <- predict(m, newdata=d)
>>> Error in model.frame.default(Terms, newdata, na.action = na.action, xlev
>>> =
>>> object$xlevels) : factor z has new levels a
>>>
>>> It seems a bug to me, although one could argue that 'lm's documentation
>>> does not allow one to expect that the '-' operator should work generally.
>>>
>>> If it is a bug I'm happy to report it to bugzilla.
>>>
>>> Thanks for all your efforts,
>>> Mark
>>>
>>> ps: I was not able to test this on R3.4.4 yet, but the NEWS does not
>>> mention fixes related to 'lm' or 'predict'.
>>>
>>>
>>> > sessionInfo()
>>> R version 3.4.3 (2017-11-30)
>>> Platform: x86_64-pc-linux-gnu (64-bit)
>>> Running under: Ubuntu 16.04.4 LTS
>>>
>>> Matrix products: default
>>> BLAS: /usr/lib/libblas/libblas.so.3.6.0
>>> LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
>>>
>>> locale:
>>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
>>> LC_TIME=nl_NL.UTF-8 LC_COLLATE=en_US.UTF-8
>>> [5] LC_MONETARY=nl_NL.UTF-8 LC_MESSAGES=en_US.UTF-8
>>> LC_PAPER=nl_NL.UTF-8 LC_NAME=C
>>> [9] LC_ADDRESS=C LC_TELEPHONE=C
>>> LC_MEASUREMENT=nl_NL.UTF-8 LC_IDENTIFICATION=C
>>>
>>> attached base packages:
>>> [1] stats graphics grDevices utils datasets methods base
>>>
>>> loaded via a namespace (and not attached):
>>> [1] compiler_3.4.3 tools_3.4.3 yaml_2.1.16
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> R-devel at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>>
>>
>>
>>
>> --
>> Joris Meys
>> Statistical consultant
>>
>> Department of Data Analysis and Mathematical Modelling
>> Ghent University
>> Coupure Links 653, B-9000 Gent (Belgium)
>>
>> <https://maps.google.com/?q=Coupure+links+653,%C2%A0B-9000+Gent,%C2%A0Belgium&entry=gmail&source=g>
>>
>> -----------
>> Biowiskundedagen 2017-2018
>> http://www.biowiskundedagen.ugent.be/
>>
>> -------------------------------
>> Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php
>>
>
--
Joris Meys
Statistical consultant
Department of Data Analysis and Mathematical Modelling
Ghent University
Coupure Links 653, B-9000 Gent (Belgium)
<https://maps.google.com/?q=Coupure+links+653,%C2%A0B-9000+Gent,%C2%A0Belgium&entry=gmail&source=g>
-----------
Biowiskundedagen 2017-2018
http://www.biowiskundedagen.ugent.be/
-------------------------------
Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php
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