Hello Jim,

thanks a lot for your help and notes. it is finally working . ;)

I am not still very experienced in this area and maybe you could please help me for some short questions as below:

1. what does mean DF SS MS when I use nlm ["ANOVATable"] .I tried to find relevant information in Mathematica tutorial. May you please share any data or let me know from where I can understand these issues?

2. I used an analytical model for my curve fitting as: model = (A + B x^n) (1 + C(Log[y] - k))* and after that I could find the variables (A,B,n,C,D**).

   Now, I want to evaluate the accuracy of my fitting process. in this case:

2-1. When I use nlm ["SinglePredictionConfidenceIntervalTable"] the difference between Observed and Predicted are very small and the corresponding Standard Error is also very small, around 1 even though smaller. Also, there is a good agreement between Experimental data and predicted values. In this point of view, the fitting process seems fine. Isn't it?

2-2. When I use nlm ["ParameterTable"] then the Standard Error relating the variables (A,B,n,C,D) are very high around 10e8. In this point of view, the fitting process seems not good.

I am confused of these tow different issues of Standard Error in items 2-1 and 2-2.

May I ask you please let me know if you have already and previous experience concerning to this issue.

Thanks in advance, Hassan

Dear Sander,

I think the best one is ''Multivariate fitting'' .