[SciPy-User] [SciPy-user] Covariance matrix
suzana8447
k-assem84@hotmail....
Wed Feb 15 07:36:59 CST 2012
Thanks all for your help.
What I have understood is that I get what so called the cov_x from least
square root fit and then multipy this matrix by the error variance.
I have two more questions.
1) What is meant by the error variance? How one can extract it?
2) Do you mean by ||err||= func-data?
Thanks in advance.
Charles R Harris wrote:
>
> On Mon, Feb 13, 2012 at 8:56 AM, <josef.pktd@gmail.com> wrote:
>
>> On Sat, Feb 11, 2012 at 7:39 PM, Kevin Gullikson
>> <kevin.gullikson@gmail.com> wrote:
>> > Use full_output=True when you call leastq, and you will get a matrix
>> (among
>> > other things). If you multiply that matrix by the standard deviation of
>> the
>> > residuals, it will be the covariance matrix.
>>
>> As Charles pointed out, multiply by the error variance not the
>> standard deviation. Docstring is wrong in this.
>>
>>
> Even more precisely, multiply by ||err||^2/(n - dof), since it is possible
> that the error has an offset unless the model can perfectly fit a
> constant.
> If this actually makes a difference, the model is inadequate, but the
> variance estimate might be useful if you are using something like the
> Akaike information criterion to choose the number of parameters.
>
> <snip>
>
> Chuck
>
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