I'm getting confused with the concept R uses to do regression using lm.

I'm afmiliar with gnuplot and the build-in fit command, but couldn't get

R's lm to work on my data.

I know that my data follows a powerlaw or maybe an exponential function,

and I'd like to determine the best fitting factors for the formula:

a*x^b where b < 0.

I've tried thge follwoing:

s <- lm(y ~ x)

summary(s)

Call:lm(formula = y ~ x)

Residuals:

Min 1Q Median 3Q Max

-18.454 -7.577 -2.861 3.909 60.988

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 21.209171 1.431472 14.816 < 2e-16 ***

x -0.065609 0.008799 -7.456 7.45e-12 ***

---

Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 11.87 on 145 degrees of freedom

Multiple R-Squared: 0.2772, Adjusted R-squared: 0.2722

F-statistic: 55.6 on 1 and 145 DF, p-value: 7.454e-12

What has R done? I assume the formula is just a+b*x and I can get a and

b via

coef(s)

(Intercept) x21.20917074 -0.06560878

But:

s <- lm(y ~ a*x^b)

Error in terms.formula(formula, data = data) :invalid power in formula

I went through the formula section of the R-manual, but I realy don't

get it.

Finally, I'd like to have the raw data-points together with a line

representing the function used to fit the data in a plot? How can I plot

function, e.g. sin(x) ?

I hope I just need a primer on this to get going.

thanks very much for any help,

Arne

--

Arne Mueller

Biomolecular Modelling Laboratory

Imperial Cancer Research Fund

44 Lincoln's Inn Fields

London WC2A 3PX, U.K.

phone : +44-(0)207 2693405 | fax :+44-(0)207-269-3534

email : a.mueller at icrf.icnet.uk | http://www.bmm.icnet.uk

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