**one_monk:**

Hi everybody,

I want to solve one task with linear regression:

I have the function

y = ax1 + bx2 + cx3 + dx4 + ex5 + fx6

y and x1 to x6 are known and I have the matrix with their empiric values (100 examples).

I want to calculate the approximation of a to f. I download the library "alglib.mqh" which must be useful.

Can somebody tell me how to calculate my task - some code will be useful. Thanks!

You are confusing something.

If you are talking about linear regression, then maybe you have 6 points (x1,y1) ...(x6,y6) and you need to find a and b in the formula of the line (y=a+b*x), at which the value of the sum of the standard deviation from the known points is minimal.

**linear regression (first-degree polynomial y=a+b*x): **

**parabolic regression (second-degree polynomial ****y=a+b*x+c*x****²):**

**wave regression (third-degree polynomial y=a+b*x+c*x²+d*x³) :**

Hi everybody,

I want to solve one task with linear regression:

I have the function

y = ax1 + bx2 + cx3 + dx4 + ex5 + fx6

y and x1 to x6 are known and I have the matrix with their empiric values (100 examples).

I want to calculate the approximation of a to f. I download the library "alglib.mqh" which must be useful.

Can somebody tell me how to calculate my task - some code will be useful. Thanks!