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  • $\begingroup$ 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? $\endgroup$ Commented Jan 28, 2019 at 17:42
  • $\begingroup$ Colleagues, let us call things by their proper names. The answer of @Coolwater is not bad, but is not optimal. $\endgroup$ Commented Jan 28, 2019 at 18:40
  • $\begingroup$ 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. $\endgroup$ Commented Jan 28, 2019 at 19:01
  • $\begingroup$ You can see it at dropbox.com/s/o08c8x0cm0dutcl/deep%20fit.pdf?dl=0 . $\endgroup$ Commented Jan 28, 2019 at 19:50
  • $\begingroup$ 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? $\endgroup$ Commented Jan 28, 2019 at 20:17