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Timeline for How to fit the data?

Current License: CC BY-SA 4.0

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Jan 29, 2019 at 12:37 comment added user64494 Hope you are sure now that Maple produces an optimal solution, you don't.
Jan 28, 2019 at 20:20 comment added Coolwater @user64494 They are the output from maple
Jan 28, 2019 at 20:17 comment added user64494 From where "Alternative start values {a,}, {b, 1.7195,}, {c, 2.3092,}, {d, 1.5033}, {e, 1.845}" which lead to {a -> 2.6174825, b -> 1.7194932, c -> 2.3092448, d -> 1.5033314, e -> 1.845972}} are taken?
Jan 28, 2019 at 19:50 comment added user64494 You can see it at dropbox.com/s/o08c8x0cm0dutcl/deep%20fit.pdf?dl=0 .
Jan 28, 2019 at 19:01 comment added user64494 That's interesting, but for $[a= 2.61748239217892,b= 1.71949328471199,c= 2.30924398627606,d= 1.50333104215966,e= 1.84597270613482]$ the sum of squared residuals equals $0.0000627585700895793 $. Hope you feel the difference.
Jan 28, 2019 at 18:57 history edited Coolwater CC BY-SA 4.0
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Jan 28, 2019 at 18:40 comment added user64494 Colleagues, let us call things by their proper names. The answer of @Coolwater is not bad, but is not optimal.
Jan 28, 2019 at 17:42 comment added user64494 Thank you. Likely a somewhat better fit than your $2.75699 \cosh \left(1.66039 x^{2.92883} \sin \left(4.74005 x^{0.70619}\right)\right) $ is $[a= 2.61748239217892,b= 1.71949328471199,c= 2.30924398627606,d= 1.50333104215966,e= 1.84597270613482]$. Can you kindly compare the results?
Jan 28, 2019 at 17:21 history answered Coolwater CC BY-SA 4.0