R help - Nov 2013 - Find the prediction or the fitted values for an lm model

Hi,

   I would like to fit my data with a 4th order polynomial. Now I have only
5 data point, I should have a polynomial that exactly pass the five point

   Then I would like to compute the "fitted" or "predict"
value with a
relatively large x dataset. How can I do it?

   BTW, I thought the model "prodfn" should pass by (0,0), but I just
wonder why the const is unequal to zero

x1<-c(0,3,4,5,8)
y1<-c(0,1,4,7,8)
prodfn<-lm(y1 ~ poly(x1, 4))

x<-seq(0,8,0.01)

temp<-predict(prodfn,data.frame(x=x))   # This line does not work..

> prodfn
Call:
lm(formula = y1 ~ poly(x1, 4))

Coefficients:
 (Intercept)  poly(x1, 4)1  poly(x1, 4)2  poly(x1, 4)3  poly(x1, 4)4
   4.000e+00     6.517e+00    -4.918e-16    -2.744e+00    -8.882e-16

	[[alternative HTML version deleted]]

On Thu, 28 Nov 2013, jpm miao wrote:
> Hi,
>
>   I would like to fit my data with a 4th order polynomial. Now I have only
> 5 data point, I should have a polynomial that exactly pass the five point
>
>   Then I would like to compute the "fitted" or
"predict" value with a
> relatively large x dataset. How can I do it?
>
>   BTW, I thought the model "prodfn" should pass by (0,0), but I
just
> wonder why the const is unequal to zero
>
> x1<-c(0,3,4,5,8)
> y1<-c(0,1,4,7,8)
> prodfn<-lm(y1 ~ poly(x1, 4))
>
> x<-seq(0,8,0.01)
>
> temp<-predict(prodfn,data.frame(x=x))   # This line does not work..
You need to call the variable x1 because that is the name you used in the 
original data:

plot(x, predict(prodfn,data.frame(x1=x)), type = "l")
points(x1, y1)
>
>> prodfn
>
> Call:
> lm(formula = y1 ~ poly(x1, 4))
>
> Coefficients:
> (Intercept)  poly(x1, 4)1  poly(x1, 4)2  poly(x1, 4)3  poly(x1, 4)4
>   4.000e+00     6.517e+00    -4.918e-16    -2.744e+00    -8.882e-16
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> 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.
>

See in-line below.

On 11/28/13 20:50, jpm miao wrote:
> Hi,
>
>     I would like to fit my data with a 4th order polynomial. Now I have
only
> 5 data point, I should have a polynomial that exactly pass the five point
>
>     Then I would like to compute the "fitted" or
"predict" value with a
> relatively large x dataset. How can I do it?
>
>     BTW, I thought the model "prodfn" should pass by (0,0), but I
just
> wonder why the const is unequal to zero
Because poly() produces orthonormalized polynomials,  Look at poly(x1,4).
It is not much like cbind(x1,x1^2,x1^3,x1^4), is it?

     cheers,

     Rolf Turner
>
> x1<-c(0,3,4,5,8)
> y1<-c(0,1,4,7,8)
> prodfn<-lm(y1 ~ poly(x1, 4))
>
> x<-seq(0,8,0.01)
>
> temp<-predict(prodfn,data.frame(x=x))   # This line does not work..
>
>
>> prodfn
> Call:
> lm(formula = y1 ~ poly(x1, 4))
>
> Coefficients:
>   (Intercept)  poly(x1, 4)1  poly(x1, 4)2  poly(x1, 4)3  poly(x1, 4)4
>     4.000e+00     6.517e+00    -4.918e-16    -2.744e+00    -8.882e-16
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> 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.