We have an example in this link:

https://www.mathworks.com/help/matlab/ref/polyfit.html?s_tid=srchtitle

Best regards

there is some way to trace variable's value of functions in matlab.

1- Use debugging mode by put break points in the appropriate place.

2- Put variables in the output argument of function.

You can fit a polynomial to your data by using the MATLAB function polyfit.

p = polyfit(x,y,n) finds the coefficients of a polynomial p(x) of degree n that fits the data, p(x(i)) to y(i), in a least squares sense.

Refer to mathworks.com for more help or type "help polyfit" at the MATLAB prompt.

Once you have used p = polyfit(x,y,n) in your program, then you should be able to use the variable p in your program. p will be a vector whose components are the coefficients which you require.

The question is not clear, U want to know the method of getting value of the parameters by fitting your experimental value to a particular curve or you want to know how use already evaluated parameter values in further evaluations.

For the first one, there are many numerical methods available based on which you can write codes in matlab. Method suggested by kandhadai is limited to polynomials only. If the your model consists of transcedental functions then other methods like newton raphson, ranga kutta are very popular and easy too.

I think the second problem is quite easy. You can assign the value to the parameters or coefficients obtained after fitting and then use the assigned values in the next code.

It sounds to me like you are using the curvefitting toolbox GUI to fit your curve. If so, you can generate a function from the GUI which can be used for fitting other curves to the same function.

Subsequently, you can retrieve the fitted parameters using the "coeffvalues" function on the cfit object. In the autogenerated code the cfit object is called cf_. Thus, to retrieve the parameters you must include the following line at the end of the code:

pars = coeffvalues(cf_);

Finally, you must modify the code so pars is passed as a function output:

change function createFit(x,y) to function[pars] = createFit(x,y).

In cftool GUI first choose "fitting" after that in fitting window

choose "newfit" in Type of fit choose "Interpolant" from Interpolant list choose

choose "shape-preserving" then press "Apply" finally to have

function in work space press "Save to workspace" and press ok.

the function you need in workspace is named "fittedmodel1"

fittedmodel1 is acting as a function and you the function value for every arbitrari x value. for example for knowing the value of function at x=0.27, you type in:

>>fittedmodel1(0.27)

By putting this function in a loop you can generate your x,y points for an arbitrary x interval: for example for x=[1, 575] you can have this:

>> for i=1:1:575;

y(i,1)=fittedmodel1(i);

>>end

in this case you will nolonger need to know the coeficients of equation.

I hope it would be useful for you.

Dear Sir,

suppose you have the following data:

x=[0.9 1.5 3 4 6 8 9.5];

y=[0.9 1.5 2.5 5.1 4.5 4.9 6.3];

Curve fitting with polynomials is done in MATLAB with the polyfit

function, which uses the least squares method. The basic form of the polyfit

function is:

For the same set of m points, the polyfit function can be used to fit polynomials

of any order up to m-1 . If n = 1 the polynomial is a straight line, if n = 2

the polynomial is a parabola, and so on. The polynomial passes through all the

points if n=m-1  (the order of the polynomial is one less than the number of

points). It should be pointed out here that a polynomial that passes through all the

points, or polynomials with higher order, do not necessarily give a better fit overall.

High-order polynomials can deviate significantly between the data points.

p = polyfit(x,y,n)

x is a vector with the horizontal coordinates

of the data points (independent variable).

y is a vector with the vertical coordinates of

the data points (dependent variable).

n is the degree of the polynomial.

p is the vector of the coefficients

of the polynomial

that fits the data. 

p=polyfit(x,y,3)

xp=0.9:0.1:9.5;

yp=polyval(p,xp);

plot(x,y,'o',xp,yp)

xlabel('x'); ylabel('y')

See page page 267-274 , if you need any help just ask, please.

Hazim

 @Hazim Hashim Tahir. Dear sir, i need your help in solving this problem

Dear Ahmed,

attached is the full matlab program( done on MATLAB Version 7.13.0.564 (R2011b)) + the graph ( the curve fit),  I want you to read all notes(comments inside the program to understand !! you will get all the coefficients on the command window.

Dear Mohammedzadeh,

You can use the following code to get the coefficients (e.g. a and b of linear model).

ftr=fittype('a*x+b');coeffnames(ftr);[curveL,gof1]=fit(x1',y1',ftr);

a1=curveL.a

b1=curveL.b

where x1 represents vector of independent data and y1 represents vector of dependent data i.e. you have to put values for the two vectors.

Hazim Hashim Tahir Dear sir,

I have two matrix of x=size(229x12) and y=size(229x1) in the 'table' format.

Is there any way to fit two vectors of x and y with different sizes?

Ressol Shakir Thank you. very good answer

For example:

c = fit(x,y,'exp1');

p=coeffvalues(c);

Be careful with fit:

X,Y must be a matrix with one or two columns.

Therefore, you can have the values of the two coefficients p(1) and p(2) and continue with the code

you also can use curvefitting toolbox "cftool". It has complete tools for curve fitting. but if your coefficient is too complex, I recomend to use optimization algorithm for example "gatool". but first you should write objective function is such a way that the curve fitting coefficient should be optimization parameter.

With the polyfit function

We have an example in this link:

https://www.mathworks.com/help/matlab/ref/polyfit.html?s_tid=srchtitle

Best regards

Kindly check https://www.mathworks.com/help/curvefit/curve-fitting.html