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Groups > comp.lang.python > #36421
| From | Terry Reedy <tjreedy@udel.edu> |
|---|---|
| Subject | Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] |
| Date | 2013-01-08 04:07 -0500 |
| References | (3 earlier) <50ea58f0$0$21851$c3e8da3$76491128@news.astraweb.com> <mailman.223.1357572059.2939.python-list@python.org> <50eb0cd2$0$30003$c3e8da3$5496439d@news.astraweb.com> <mailman.239.1357597977.2939.python-list@python.org> <50eb7513$0$30003$c3e8da3$5496439d@news.astraweb.com> |
| Newsgroups | comp.lang.python |
| Message-ID | <mailman.268.1357636078.2939.python-list@python.org> (permalink) |
On 1/7/2013 8:23 PM, Steven D'Aprano wrote: > On Mon, 07 Jan 2013 22:32:54 +0000, Oscar Benjamin wrote: > >> An example: Earlier today I was looking at some experimental data. A >> simple model of the process underlying the experiment suggests that two >> variables x and y will vary in direct proportion to one another and the >> data broadly reflects this. However, at this stage there is some >> non-normal variability in the data, caused by experimental difficulties. >> A subset of the data appears to closely follow a well defined linear >> pattern but there are outliers and the pattern breaks down in an >> asymmetric way at larger x and y values. At some later time either the >> sources of experimental variation will be reduced, or they will be >> better understood but for now it is still useful to estimate the >> constant of proportionality in order to check whether it seems >> consistent with the observed values of z. With this particular dataset I >> would have wasted a lot of time if I had tried to find a computational >> method to match the line that to me was very visible so I chose the line >> visually. > > > If you mean: > > "I looked at the data, identified that the range a < x < b looks linear > and the range x > b does not, then used least squares (or some other > recognised, objective technique for fitting a line) to the data in that > linear range" > > then I'm completely cool with that. If both x and y are measured values, then regressing x on y and y on x with give different answers and both will be wrong in that *neither* will be the best answer for the relationship between them. Oscar did not specify whether either was an experimentally set input variable. > But that is not fitting a line by eye, which is what I am talking about. With the line constrained to go through 0,0, a line eyeballed with a clear ruler could easily be better than either regression line, as a human will tend to minimize the deviations *perpendicular to the line*, which is the proper thing to do (assuming both variables are measured in the same units). -- Terry Jan Reedy
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Numpy outlier removal "Joseph L. Casale" <jcasale@activenetwerx.com> - 2013-01-06 19:44 +0000
Re: Numpy outlier removal Hans Mulder <hansmu@xs4all.nl> - 2013-01-06 23:33 +0100
RE: Numpy outlier removal "Joseph L. Casale" <jcasale@activenetwerx.com> - 2013-01-06 22:50 +0000
Re: Numpy outlier removal MRAB <python@mrabarnett.plus.com> - 2013-01-06 23:18 +0000
Re: Numpy outlier removal Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2013-01-07 01:46 +0000
Re: Numpy outlier removal "Paul Simon" <psimon@sonic.net> - 2013-01-06 18:21 -0800
Re: Numpy outlier removal Oscar Benjamin <oscar.j.benjamin@gmail.com> - 2013-01-07 02:29 +0000
Re: Numpy outlier removal Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2013-01-07 05:11 +0000
Re: Numpy outlier removal Oscar Benjamin <oscar.j.benjamin@gmail.com> - 2013-01-07 15:20 +0000
[Offtopic] Line fitting [was Re: Numpy outlier removal] Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2013-01-07 17:58 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Chris Angelico <rosuav@gmail.com> - 2013-01-08 06:43 +1100
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2013-01-08 02:06 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Chris Angelico <rosuav@gmail.com> - 2013-01-08 17:35 +1100
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Robert Kern <robert.kern@gmail.com> - 2013-01-08 15:55 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Chris Angelico <rosuav@gmail.com> - 2013-01-09 07:14 +1100
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2013-01-09 07:50 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Robert Kern <robert.kern@gmail.com> - 2013-01-08 22:59 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Oscar Benjamin <oscar.j.benjamin@gmail.com> - 2013-01-07 22:32 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2013-01-08 01:23 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Terry Reedy <tjreedy@udel.edu> - 2013-01-08 04:07 -0500
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Maarten <maarten.sneep@knmi.nl> - 2013-01-08 08:47 -0800
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Maarten <maarten.sneep@knmi.nl> - 2013-01-08 08:47 -0800
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2013-01-09 00:02 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Oscar Benjamin <oscar.j.benjamin@gmail.com> - 2013-01-08 13:50 +0000
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Jason Friedman <jason@powerpull.net> - 2013-01-08 19:22 -0700
Re: [Offtopic] Line fitting [was Re: Numpy outlier removal] Jason Friedman <jason@powerpull.net> - 2013-01-08 19:23 -0700
Re: Numpy outlier removal Robert Kern <robert.kern@gmail.com> - 2013-01-07 15:35 +0000
RE: Numpy outlier removal "Joseph L. Casale" <jcasale@activenetwerx.com> - 2013-01-07 02:12 +0000
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