Question: nonlinear fit gives the right fit, but wrong parameters

hello im currently working on a project and im fitting some non-linear data with the follwing model:

model:= 1.*10^5*exp(-t*k-*t/B)

where B and k are the unkown parameters.

i have the following data:


Y := <100000, 86089.76983, 74114.4849, 63804.98946, 54929.56828>

if i do the fit like this: fit(model,X,Y,t) i get a fit that looks like this:

100000*exp(-0.520664970792415e-1*t) which i alright. however when i try to get the parameters i get something like this


[B = .999563650781966, k = -.948370042622550] - when i define k=0.05 however i get [B = 483.910474528817], which is the right parameter.

insereting the two different sets yields:

1) k=0.05, B = 483.910474528817 -> 100000*exp(-0.520664970792415e-1*t) (good aprox to the fit)

2) B = .999563650781966 and k = -.948370042622550 -> 100000*exp(-0.5206649794e-1*S) (way off)

how is this possible anyone able to help, been sitting with this for days now?



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