Timeline for LinearFit, are constraints possible?
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| Mar 21, 2017 at 16:33 | comment | added | SPIL | If I change my data set to: {{25.32, 0., 0., 0., 0., 0., 0., 607}, {25.32, 0., 0., 0., 13.36, 0., 0., 1282}, {25.32, 0., 0., 0., 13.36, 0., 8.69, 1627}, {25.32, 13.21, 0., 0., 13.36, 0., 8.69, 2143}, {25, 13.21, 0., 8.94, 13.36, 0., 8.69, 2109}, {25.32, 13.21, 0., 8.94, 13.36, 0., 8.69, 2170}}, so now values not one or zero but other values. Could I apply the same method, as the two correct answers below? Thank you | |
| Mar 21, 2017 at 14:31 | vote | accept | SPIL | ||
| Mar 21, 2017 at 9:46 | vote | accept | SPIL | ||
| Mar 21, 2017 at 14:31 | |||||
| Mar 21, 2017 at 4:43 | answer | added | kglr | timeline score: 3 | |
| Mar 20, 2017 at 23:06 | answer | added | JimB | timeline score: 4 | |
| Mar 20, 2017 at 21:03 | comment | added | george2079 |
my column elimination result is the same as the full result (with error message) if you insert x1->1 , by the way.
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| Mar 20, 2017 at 20:49 | comment | added | george2079 |
this removes the error, eliminate columns where the data has only a single value LinearModelFit[data[[All, {2, 4, 5, 7, 8}]] , {x2, x4, x5, x7}, {x2, x4, x5, x7}] You do not have enough information to say anything about the missing terms.
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| Mar 20, 2017 at 18:54 | comment | added | JimB |
Yes. Just create your data in the form {x1,x2+x3+x4,x5+x6+x7}. But even then you have 5 parameters to estimate with just 6 sample points.
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| Mar 20, 2017 at 18:21 | history | edited | corey979 | CC BY-SA 3.0 |
deleted 9 characters in body
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| Mar 20, 2017 at 17:52 | history | asked | SPIL | CC BY-SA 3.0 |