data fitting

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06-04-2013 07:04 AM
irinivozinaki
New Contributor III
Hello everyone...

I am really confused and I would like to ask some help from you.

I have a dependent variable named "D"
and two independent variables named "V" and "H"

The D variable can take the values 1 or 2 or 3 or 4 or 5

The H variable values can be H1, H2, H3, H4
Same for V variable which takes the values V1, V2, V3

I have several triads of data as for example:

H1, V1, 1
H1, V2, 3
H1, V1, 2
H1, V2, 2
H3, V4, 5

etc...

I have attached an image as an example in order to explain better the problem.

I would like to see which are the curves fitting these data. But I can't decide the way to do it.


I have studied a little logistic regression... polytomous logistic regression specifically, but I am not sure that it can help me...

Hope that you can understand what i am looking for... thank you very much in advance for your help.







I have sets of data in the form (H,
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ShaunWalbridge
Esri Regular Contributor
This question really isn't about Python nor spatial statistics, so you're unlikely to get an in-depth response here. You might want to try [Cross Validated](http://stats.stackexchange.com/) for this kind of question. If you have other ancillary data that is spatial, you might be interested in this tool to link ArcGIS with R which lets you connect ArcGIS with R, which may be useful.
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