Re: NonlinearFit-Logistic Function-CalcCenter 3
- To: mathgroup at smc.vnet.net
- Subject: [mg60567] Re: NonlinearFit-Logistic Function-CalcCenter 3
- From: "Ray Koopman" <koopman at sfu.ca>
- Date: Tue, 20 Sep 2005 05:19:58 -0400 (EDT)
- References: <dgitnd$2e2$1@smc.vnet.net>
- Sender: owner-wri-mathgroup at wolfram.com
Oddur Bjarnason wrote:
> I thank Bob Hanlon and Valeri Astanoff for their prompt reply and am following their suggestions.
>
> Purely by chance I found a solution to the problem I had using CalcCenter 3 for nonlinear fitting of data to a logistic function.
>
> By fitting
>
> data2={{-0.08,0.05},{0.96,-3.19},
> {1.93,-6.4},{2.98,-10.32},
> {3.97,-11.8},{5.92,-13.98},
> {7.88,-14.12},{11.85,-15.34},
> {15.79,-14.61},{19.7,-15.43},
> {23.67,-15.83}};
>
> by NonlinearFit[data2, -a/(1 + b*Exp[-c*t]), t, {a, b, c}]
>
> instead of
>
> NonlinearFit[data2, a/(1 + b*Exp[-c*t]), t, {a, b, c}]
>
> that is by changing the sign of a
>
> I obtained the function
>
> -14.917794621733984/(1 + 10.284628991516529*Exp[-1.0072061447043623*t]
>
> Presumably this method can also be used in Mathematica.
>
> I must admit that I have not as yet found out why this works.
>
> Regards,
>
> Oddur Bjarnason
I have found the logistic function to be generally more tractable
if it is parameterized using Log[b] instead of b:
In[1]:= data2={{-.08,.05},{.96,-3.19},{1.93,-6.4},{2.98,-10.32},
{3.97,-11.8},{5.92,-13.98},{7.88,-14.12},{11.85,-15.34},
{15.79,-14.61},{19.7,-15.43},{23.67,-15.83}};
In[2]:= altexpr = a/(1 + Exp[d-c*t]); altparam = {a,d,c};
In[3]:= FindFit[data2, altexpr, altparam, t]
FindFit[data2, altexpr, altparam, t, Method->QuasiNewton]
FindFit[data2, altexpr, altparam, t, Method->Gradient]
Exp[d/.%]
Out[3]= {a -> -14.9178, d -> 2.33065, c -> 1.00721}
Out[4]= {a -> -14.9178, d -> 2.33065, c -> 1.00721}
Out[5]= {a -> -14.9178, d -> 2.33064, c -> 1.0072}
Out[6]= 10.2845