Quasi-Newton least squares method: user defined fit

You have the possibility to fit data of your own or let the program generate the data from your specifications. In the first case your input x serves as your initial guess for the optimal parameter and otherwise it is used for the data generation as the unperturbed solution.

Please type here an identification text used for the plot:

Please specify the number of coefficients n here:

Number of fit coefficients n =

Important: 1 <= n <= 20 !

Please write a piece of code for the computation of f(x;t) in the following field.
The coefficients appear as x(1) ... x(n) and the ''free'' variable is t:
The input parameters are n, x, t and the result must be named as yt! You may use here prefdefined real variables x1h,x2h,x3h,x4h,x5h,x6h,x7h,x8h,x9h,y(100), the integers i,j,k and logical variables bool1,bool2,bool3. All these variables are initialized with 0 resp. .false. There are also available the constants pi, sqrt2(=sqrt(2.d0)),e1(=exp(1.0d0)). The restrictions of JAKEF apply here!

Initial (for own data) or true vector (for data generation): x(1),...,x(n)

x=	1,2,1.2,0.2

Do you want to fit data of your own or should the program generate data artificially?

internally generated	Number m of data points: m = Important: n <= m <= 200 ! The interval for t: a = b = The perturbation level for the data y: level = Important: 0 <= level <= 1 !
Own data	Number m of data points: m = Important: n<= m <= 200 ! Please type your data in the textarea, m pairs of numbers, not necessarily each on a new line for example: 0,0, 1,1 2,1.4 and so on.

Warning!!! - This may take some time.

Click on "evaluate", in order to submit your input.