I wonder how one in R can fit a 3rd degree polynomial to some data? Say the data is: y <- c(15.51, 12.44, 31.5, 21.5, 17.89, 27.09, 15.02, 13.43, 18.18, 11.32) x <- seq(3.75, 6, 0.25) And resulting degrees of polynomial are: 5.8007 -91.6339 472.1726 -774.2584 THanks in advance! -- Jonas Malmros Stockholm University Stockholm, Sweden
try this:
y <- c(15.51, 12.44, 31.5, 21.5, 17.89, 27.09, 15.02, 13.43, 18.18,
11.32)
x <- seq(3.75, 6, 0.25)
coef(lm(y ~ x + I(x^2) + I(x^3)))
I hope it helps.
Best,
Dimitris
----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
----- Original Message -----
From: "Jonas Malmros" <jonas.malmros at gmail.com>
To: <r-help at r-project.org>
Sent: Monday, January 07, 2008 4:15 PM
Subject: [R] Polynomial fitting
>I wonder how one in R can fit a 3rd degree polynomial to some data?
>
> Say the data is:
>
> y <- c(15.51, 12.44, 31.5, 21.5, 17.89, 27.09, 15.02, 13.43, 18.18,
> 11.32)
> x <- seq(3.75, 6, 0.25)
>
> And resulting degrees of polynomial are:
>
> 5.8007 -91.6339 472.1726 -774.2584
>
> THanks in advance!
>
>
>
> --
> Jonas Malmros
> Stockholm University
> Stockholm, Sweden
>
> ______________________________________________
> 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.
>
Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm
Jonas,
In statistical sense polynomial is a linear regression fit. The function
that handles linear fitting is called lm. Here is how you can reproduce
your results:
lm(y ~ x + I(x^2) + I(x^3))
Unless you are really after the polynomial coefficients it is probably
better to use orthogonal polynomials. You can get this fit by doing
lm(y ~ poly(x, 3))
Check out help pages for lm and poly. Hope this helps,
Andy
__________________________________
Andy Jaworski
518-1-01
Process Laboratory
3M Corporate Research Laboratory
-----
E-mail: apjaworski at mmm.com
Tel: (651) 733-6092
Fax: (651) 736-3122
"Jonas Malmros"
<jonas.malmros at gm
ail.com> To
Sent by: r-help at r-project.org
r-help-bounces at r- cc
project.org
Subject
[R] Polynomial fitting
01/07/2008 09:16
AM
I wonder how one in R can fit a 3rd degree polynomial to some data?
Say the data is:
y <- c(15.51, 12.44, 31.5, 21.5, 17.89, 27.09, 15.02, 13.43, 18.18, 11.32)
x <- seq(3.75, 6, 0.25)
And resulting degrees of polynomial are:
5.8007 -91.6339 472.1726 -774.2584
THanks in advance!
--
Jonas Malmros
Stockholm University
Stockholm, Sweden
______________________________________________
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.
On Mon, 7 Jan 2008, apjaworski at mmm.com wrote:> Jonas, > > In statistical sense polynomial is a linear regression fit. The function > that handles linear fitting is called lm. Here is how you can reproduce > your results: > > lm(y ~ x + I(x^2) + I(x^3)) > > Unless you are really after the polynomial coefficients it is probably > better to use orthogonal polynomials. You can get this fit by doing > > lm(y ~ poly(x, 3))And if you are, y ~ poly(x, 3, raw=TRUE) is simpler to type and comprehend.> > Check out help pages for lm and poly. Hope this helps, > > Andy > > __________________________________ > Andy Jaworski > 518-1-01 > Process Laboratory > 3M Corporate Research Laboratory > ----- > E-mail: apjaworski at mmm.com > Tel: (651) 733-6092 > Fax: (651) 736-3122 > > > > "Jonas Malmros" > <jonas.malmros at gm > ail.com> To > Sent by: r-help at r-project.org > r-help-bounces at r- cc > project.org > Subject > [R] Polynomial fitting > 01/07/2008 09:16 > AM > > > > > > > > > I wonder how one in R can fit a 3rd degree polynomial to some data? > > Say the data is: > > y <- c(15.51, 12.44, 31.5, 21.5, 17.89, 27.09, 15.02, 13.43, 18.18, 11.32) > x <- seq(3.75, 6, 0.25) > > And resulting degrees of polynomial are: > > 5.8007 -91.6339 472.1726 -774.2584 > > THanks in advance! > > > > -- > Jonas Malmros > Stockholm University > Stockholm, Sweden > > ______________________________________________ > 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. > > ______________________________________________ > 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. >-- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595