拟合 例 表 1 x  0   3   5   7   9   11   12   13   14   15 y  0 1.2 1.7 2.0 2.1 2.0 1.8 1.2 1.0 1.6 拟合求解函数表达式。
1 2 3 4  x=[0  3  5  7  9  11  12  13  14  15 ]; y=[0  1.2  1.7  2.0  2.1  2.0  1.8  1.2  1.0  1.6 ];plot (x,y)
 
1 2 3 4 5 6 7 8 9 10 x0=[0  3  5  7  9  11  12  13  14  15 ]'; y0=[0  1.2  1.7  2.0  2.1  2.0  1.8  1.2  1.0  1.6 ]';plot (x0,y0,'ro' );hold  on [p1,s1]=polyfit(x0,y0,3 ) [y,delete]=polyval(p1,x0,s1)plot (x0,y) T = table (x0,y0,y,y0-y,'VariableNames' ,{'X' ,'Y' ,'Fit' ,'FitError' })
 
$$y=0.0012x^3-0.0517x^2+0.5939x-0.0541$$
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 p1 =     0.0012    -0.0517     0.5939    -0.0541  s1 =   包含以下字段的 struct:         R: [4 ×4  double]        df: 6      normr: 0.6985  >> s1.Rans  =    1.0e+03  *    -5.4009    -0.3995    -0.0301    -0.0023           0    -0.0553    -0.0103    -0.0016           0          0    -0.0025    -0.0010           0          0          0     0.0010  delete =     0.3982      0.3397      0.3351      0.3216      0.3203      0.3236      0.3196      0.3143      0.3219      0.3701  T =   10 ×4  table      X      Y        Fit       FitError     __    ___    _________    _________      0       0     -0.054067      0.054067       3     1.2        1.2944     -0.094445       5     1.7        1.7716     -0.071558       7       2        1.9776      0.022391       9     2.1        1.9696       0.13044      11       2        1.8044       0.19564      12     1.8        1.6806       0.11936      13     1.2         1.539      -0.33899      14       1        1.3865      -0.38653      15     1.6        1.2304       0.36962 
 
参考