about fitting a regression line
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.
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