[WP34s] Linear and non-linear regression with L.R.

[Dieter]

(05-22-2014 08:07 PM)walter b Wrote:  In any of the cases covered, it's still a linear regression - either immediately or with transformed variables.

Yes, I know how the different fits are calculated. But still the result is a linear fit only in one single case. All others are non-linear. And that's how the manual states it: it does not say ln y = ln a₀ + a₁ x, but y = a₀ · e^a₁ x.

Quote:What you complain about was already taken care of in the manual v3.2 published 15 months ago. #-)

Hm. Sourceforge.net has a manual file dated 2014-02-04. The file name says "3_2.pdf" while the picture on the first page says "v. 3.1_3333". In any case it has the same text in the IOP as my version 3330: "[L.R.] returns the parameters a1 and a0 of the fit curve through the data points accumulated in the summation registers, according to the curve fit model selected (see LINF, EXPF, POWERF, and LOGF)." And that's it. If this is the version from last February, where can I find a newer version that was published a year earlier than this ?-)

Quote:BTW, from a mathematical point of view, calling the two regression coefficients a₀ and a₁ is the most general approach - you immediately know that e.g. a₁ belongs to x^1.

There are different mathematical points of view. Your example is fine for a polynomial fit, where a_n is the coefficient at xⁿ. Another common application in statistics is a multiple linear regression. Here the coefficients are also called a_n, but they refer to the variable x_n.

Quote:Thanks for reporting that. We'll look into it.

Great, thanks.

Dieter