regression(f,x,y,ic)

Performs a non linear regression of function f(x, a1, a2, ..., ak). Arrays x and y contains the data points and array ic contains the initial values of the unknown parameters.


See also regression2 linearreg_ana 


Example


To fit function f(x)=(a-c)*exp(-b*x)+c to a set of pairs (x,y) we first create a function:


f(x,a,b,c)=(a-c)*exp(-b*x)+c

f(x,a,b,c)=(a-c)*exp(-b*x)+c


The set of pairs is given by these two arrays:


x=(0,1,2,5,10,15,30,45,60)

( 0 1 2 5 10 15 30 45 60 )


y=(210,198,187,155,121,103,77,71,70)

( 210 198 187 155 121 103 77 71 70 )


Making use of function regression() we get:


regression(f,x,y)


Nonlinear Regression

Statistics:

+-----------------------+------------------+

| R squared             |          0.99973 |

| R squared adjusted    |          0.99964 |

| Df1 (regression)      |       2          |

| Df2 (error)           |       6          |

| F statistic           |      11072.71052 |

| P                     |          0.00000 |

| SSQ                   |          6.91898 |

| Log-likelihood        |        -11.58715 |

| AIC                   |          3.24159 |

| BIC                   |          3.30733 |

+-----------------------+------------------+


Computed parameters

+----+------------------+------------------+------------------+

|    |     Value        |     Std. Error   |        P         |

+----+------------------+------------------+------------------+

|  a |        210.88273 |          0.75349 |          0.00000 |

|  b |          0.09878 |          0.00190 |          0.00000 |

|  c |         69.62170 |          0.73376 |          0.00000 |

+----+------------------+------------------+------------------+


Covariance matrix

+----+------------------+------------------+------------------+

|    |         a        |         b        |         c        |

+----+------------------+------------------+------------------+

|  a |          0.56775 |          0.00076 |          0.09938 |

|  b |          0.00076 |          0.00000 |          0.00092 |

|  c |          0.09938 |          0.00092 |          0.53841 |

+----+------------------+------------------+------------------+