# [R] about fitting a regression line

Christopher W Ryan cryan at binghamton.edu
Thu Jun 15 22:07:14 CEST 2017

```Rather than just posting your error message, it helps immensely to post the
code that produced the error--indeed with some small sample data that
reproduces the problem.

x <- rnorm(40)
y <- 0.6 * x + rnorm(40, sd = 0.3)
plot(y ~ x)
model <- lm(y ~ cos(x))
summary(model)
plot(y ~ cos(x))
abline(model, col = "red")

## obviously I am not claiming that this is a meaningful or sensible model
## It's just for illustrative purposes

--Chris Ryan

On Thu, Jun 15, 2017 at 3:48 PM, lily li <chocold12 at gmail.com> wrote:

> Thanks for your replies. I tried the regression, but then got a NA value
> for the slope. And here is the error message:
> Coefficients: (1 not defined because of singularities)
>
>
> On Thu, Jun 15, 2017 at 12:20 AM, PIKAL Petr <petr.pikal at precheza.cz>
> wrote:
>
> > Hi
> >
> > But X can be some function like - sin, cos, log, exp...
> >
> > Cheers
> > Petr
> >
> > > -----Original Message-----
> > > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of lily
> li
> > > Sent: Thursday, June 15, 2017 1:28 AM
> > > To: MacQueen, Don <macqueen1 at llnl.gov>
> > > Cc: R mailing list <r-help at r-project.org>
> > > Subject: Re: [R] about fitting a regression line
> > >
> > > Thanks. I thought lm() function is for linear model, such as the
> > correlation
> > > below:
> > > Y= aX + b
> > >
> > > On Wed, Jun 14, 2017 at 5:25 PM, MacQueen, Don <macqueen1 at llnl.gov>
> > > wrote:
> > >
> > > > Start with the lm() function; i.e., see
> > > >
> > > >   ?lm
> > > >
> > > > -Don
> > > >
> > > > --
> > > > Don MacQueen
> > > >
> > > > Lawrence Livermore National Laboratory
> > > > 7000 East Ave., L-627
> > > > Livermore, CA 94550
> > > > 925-423-1062
> > > >
> > > >
> > > > On 6/14/17, 3:40 PM, "R-help on behalf of lily li" <
> > > > r-help-bounces at r-project.org on behalf of chocold12 at gmail.com>
> wrote:
> > > >
> > > >     Hi R users,
> > > >
> > > >     I have some data points (Xi, Yi), and they may follow such a
> > > > pattern Yi =
> > > >     cCOS(Xi) + d, how to find the c and d in R? which function to
> use?
> > > > Also,
> > > >     how to get the R2 and p value for this correlation? Thanks for
> any
> > > > kind of
> > > >     help.
> > > >
> > > >         [[alternative HTML version deleted]]
> > > >
> > > >     ______________________________________________
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> code.
> > > >
> > > >
> > > >
> > >
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