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Barry Rowlingson

2010-Jan-18 23:31 UTC

[R] Predict polynomial problem

I have a function that fits polynomial models for the orders in n:

lmn <- function(d,n){
  models=list()
  for(i in n){
    models[[i]]=lm(y~poly(x,i),data=d)
  }
  return(models)
}

 My data is:

 > d=data.frame(x=1:10,y=runif(10))

 So first just do it for a cubic:

 > mmn = lmn(d,3)
 > predict(mmn[[3]])
        1         2         3         4         5         6         7         8
0.6228353 0.5752811 0.5319524 0.4957381 0.4695269 0.4562077 0.4586691 0.4798001
        9        10
0.5224893 0.5896255

and lets extrapolate a bit:

 > predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))
        1         2         3
 0.5224893 0.5896255 0.6840976

 now let's to it for cubic to quintic:

 > mmn = lmn(d,3:5)

 check the cubic:

 > predict(mmn[[3]])
        1         2         3         4         5         6         7         8
0.6228353 0.5752811 0.5319524 0.4957381 0.4695269 0.4562077 0.4586691 0.4798001
        9        10
0.5224893 0.5896255

 - thats the same as last time. Extrapolate?

 > predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))
Error: variable 'poly(x, i)' was fitted with type "nmatrix.3"
but type
"nmatrix.5" was supplied
In addition: Warning message:
In Z/rep(sqrt(norm2[-1L]), each = length(x)) :
  longer object length is not a multiple of shorter object length

it falls over. I can't see the difference between the objects,
summary() looks the same. Is something wrapped up in an environment
somewhere, or some lazy evaluation thing, or have I just done
something stupid?

Here's a complete example you can paste in - R --vanilla < this.R
gives the error above - R 2.10.1 on Ubuntu, and also on R 2.8.1 I had
lying around on a Windows box:

d = data.frame(x=1:10,y=runif(10))

lmn <- function(d,n){
  models=list()
  for(i in n){
    models[[i]]=lm(y~poly(x,i),data=d)
  }
  return(models)
}

mmn = lmn(d,3)
predict(mmn[[3]])
predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))

mmn2 = lmn(d,3:5)
predict(mmn2[[3]])
predict(mmn2[[3]],newdata=data.frame(x=c(9,10,11)))


Barry

Bert Gunter

2010-Jan-19 00:16 UTC

head link

[R] Predict polynomial problem

Barry:

I reproduced your error on Windows.

However, as you know, in your code below, the first two components of your
list are NULL. This is a bit clumsy, so I modified your lmn function by
changing it from 

... for(i in n) ...

to

... for( i in 1:n) ...

With that change, there are no errors.

Other than that, no clue, but maybe it helps.

-- Bert

Bert Gunter
Genentech Nonclinical Statistics

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
Behalf Of Barry Rowlingson
Sent: Monday, January 18, 2010 3:31 PM
To: r-help at r-project.org
Subject: [R] Predict polynomial problem

 I have a function that fits polynomial models for the orders in n:

lmn <- function(d,n){
  models=list()
  for(i in n){
    models[[i]]=lm(y~poly(x,i),data=d)
  }
  return(models)
}

 My data is:

 > d=data.frame(x=1:10,y=runif(10))

 So first just do it for a cubic:

 > mmn = lmn(d,3)
 > predict(mmn[[3]])
        1         2         3         4         5         6         7
8
0.6228353 0.5752811 0.5319524 0.4957381 0.4695269 0.4562077 0.4586691
0.4798001
        9        10
0.5224893 0.5896255

and lets extrapolate a bit:

 > predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))
        1         2         3
 0.5224893 0.5896255 0.6840976

 now let's to it for cubic to quintic:

 > mmn = lmn(d,3:5)

 check the cubic:

 > predict(mmn[[3]])
        1         2         3         4         5         6         7
8
0.6228353 0.5752811 0.5319524 0.4957381 0.4695269 0.4562077 0.4586691
0.4798001
        9        10
0.5224893 0.5896255

 - thats the same as last time. Extrapolate?

 > predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))
Error: variable 'poly(x, i)' was fitted with type "nmatrix.3"
but type
"nmatrix.5" was supplied
In addition: Warning message:
In Z/rep(sqrt(norm2[-1L]), each = length(x)) :
  longer object length is not a multiple of shorter object length

it falls over. I can't see the difference between the objects,
summary() looks the same. Is something wrapped up in an environment
somewhere, or some lazy evaluation thing, or have I just done
something stupid?

Here's a complete example you can paste in - R --vanilla < this.R
gives the error above - R 2.10.1 on Ubuntu, and also on R 2.8.1 I had
lying around on a Windows box:

d = data.frame(x=1:10,y=runif(10))

lmn <- function(d,n){
  models=list()
  for(i in n){
    models[[i]]=lm(y~poly(x,i),data=d)
  }
  return(models)
}

mmn = lmn(d,3)
predict(mmn[[3]])
predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))

mmn2 = lmn(d,3:5)
predict(mmn2[[3]])
predict(mmn2[[3]],newdata=data.frame(x=c(9,10,11)))


Barry

______________________________________________
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.

Charles C. Berry

2010-Jan-19 01:36 UTC

head link

[R] Predict polynomial problem

On Mon, 18 Jan 2010, Barry Rowlingson wrote:
> I have a function that fits polynomial models for the orders in n:
>
> lmn <- function(d,n){
>  models=list()
>  for(i in n){
>    models[[i]]=lm(y~poly(x,i),data=d)
>  }
>  return(models)
> }
>
> My data is:
>
> > d=data.frame(x=1:10,y=runif(10))
>
> So first just do it for a cubic:
>
> > mmn = lmn(d,3)
> > predict(mmn[[3]])
>        1         2         3         4         5         6         7       
8
> 0.6228353 0.5752811 0.5319524 0.4957381 0.4695269 0.4562077 0.4586691
0.4798001
>        9        10
> 0.5224893 0.5896255
>
> and lets extrapolate a bit:
>
> > predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))
>        1         2         3
> 0.5224893 0.5896255 0.6840976
>
> now let's to it for cubic to quintic:
>
> > mmn = lmn(d,3:5)
>
> check the cubic:
>
> > predict(mmn[[3]])
>        1         2         3         4         5         6         7       
8
> 0.6228353 0.5752811 0.5319524 0.4957381 0.4695269 0.4562077 0.4586691
0.4798001
>        9        10
> 0.5224893 0.5896255
>
> - thats the same as last time. Extrapolate?
>
> > predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))
> Error: variable 'poly(x, i)' was fitted with type
"nmatrix.3" but type
> "nmatrix.5" was supplied
> In addition: Warning message:
> In Z/rep(sqrt(norm2[-1L]), each = length(x)) :
>  longer object length is not a multiple of shorter object length
>
> it falls over. I can't see the difference between the objects,
> summary() looks the same. Is something wrapped up in an environment
> somewhere, or some lazy evaluation thing, or have I just done
> something stupid?
>
Its the environment thing.

I think you want something like this:

 	models[[i]]=lm( bquote( y ~ poly(x,.(i)) ), data=d)

Use
 	terms( mmn[[3]] )

both with and without this change and


 	ls( env = environment( formula( mmn[[3]] ) ) )
 	get("i",env=environment(formula(mmn[[3]])))
 	sapply(mmn,function(x) environment( formula( x ) ) )


to see what gives.

HTH,

Chuck
> Here's a complete example you can paste in - R --vanilla < this.R
> gives the error above - R 2.10.1 on Ubuntu, and also on R 2.8.1 I had
> lying around on a Windows box:
>
> d = data.frame(x=1:10,y=runif(10))
>
> lmn <- function(d,n){
>  models=list()
>  for(i in n){
>    models[[i]]=lm(y~poly(x,i),data=d)
>  }
>  return(models)
> }
>
> mmn = lmn(d,3)
> predict(mmn[[3]])
> predict(mmn[[3]],newdata=data.frame(x=c(9,10,11)))
>
> mmn2 = lmn(d,3:5)
> predict(mmn2[[3]])
> predict(mmn2[[3]],newdata=data.frame(x=c(9,10,11)))
>
>
> Barry
>
> ______________________________________________
> 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.
>
Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901

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