- #1

- 87

- 0

I've a very trivial numerical problem where I'm currently stuck. In MATLAB the matrix Hf:

Code:

```
>> Hf
Hf =
1.0e+003 *
1.6443 1.6516 1.6583
4.8373 4.8349 4.8334
4.6385 4.6418 4.6445
-9.6014 -9.6084 -9.6154
```

And the following vectors which are very close:

Code:

```
>> [yl1 , yl3 , yl1 - yl3 ]
ans =
1.0e+006 *
0.2966 0.2972 -0.0006
0.8705 0.8703 0.0002
0.8352 0.8355 -0.0003
-1.7288 -1.7295 0.0006
```

yl1 is my result as it should be:

Code:

```
>> Hf \ yl1
ans =
100.0000
75.0000
5.0000
```

yl3 is obtained in a different way but is very close to the original. But sill:

Code:

```
>> Hf \ yl3
ans =
56.0412
72.5578
51.4007
```

The result is not just a little bit away, it is terrible, unuseable!

I have much redundancy in the data, so I can ad much lines to the matrix Hf. However, it does not matter how much, the result is always the same ... unuseable.

Can anyone explain why the least squares is so terrible in this case? I'm a bit confused because least squares should be pretty robust ...

Thanks,

divB