[R] predicting values from multiple regression

[David Winsemius]

On Mar 20, 2011, at 3:56 PM, Anna Lee wrote:

> Dear Ista!
>
> Thank you for replying. The point you made is exactly what's the
> problem: I want to predict the values at different points in space.
> calP stands for the water content at each sampling point (n=90) but I
> don't quite understand what R does. calP is my vector of measured data
> and I thought with the predict function the programm would calculate a
> value from the model function for every value of calP... ?

I do not think you are reading Ista Zahn comments carefully. She said  
you needed to offer you newdata argument as a data.frame. That is the  
fundamental problem.

She also pointed out that your arguments in the list didn't seem to  
represent a full explorations of the data "space". If all of the  
variables in the regression problem have the same value for each case,  
then there is no point in adding multiple variables.

-- 
David.


>
> 2011/3/20 Ista Zahn <izahn at psych.rochester.edu>:
>> Hi Anna,
>>
>> On Sun, Mar 20, 2011 at 2:54 PM, Anna Lee <ana-lee at web.de> wrote:
>>> Hey List,
>>>
>>> I did a multiple regression and my final model looks as follows:
>>>
>>> model9<-lm(calP ~ nsP + I(st^2) + distPr + I(distPr^2))
>>>
>>> Now I tried to predict the values for calP from this model using the
>>> following function:
>>>
>>> xv<-seq(0,89,by=1)
>>> yv<-predict(model9,list(distPr=xv,st=xv,nsP=xv))
>>
>> The second argument to predict.lm is newdata, which should be a
>> data.frame. see ?predict.lm.
>>
>> Beyond that though, I'm not sure what you are trying to accomplish.
>> The way you've set this up you would get predicted values for cases
>> like
>>
>> distPr     st     nsp
>> 0            0      0
>> 1            1      1
>> 2            2      2
>> .             .       .
>> 89          89     89
>>
>>
>> Is that really what you want?
>>
>> Best,
>> Ista
>>>
>>> The predicted values are however strange. Now I do not know weather
>>> just the model does not fit the data (actually all coefficiets are
>>> significant and the plot(model) shows a good shape) or wether I did
>>> something wrong with my prediction command. Does anyone have an
>>> idea???
>>>
>>> --
>>>
>>>
>>> Thanks a lot, Anna
>>>
>>> ______________________________________________
>>> 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.
>>>
>>
>>
>>
>> --
>> Ista Zahn
>> Graduate student
>> University of Rochester
>> Department of Clinical and Social Psychology
>> http://yourpsyche.org
>>
>
>
>
> -- 
>
>
>
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT