[SciPy-User] [SciPy-user] Covariance matrix
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, <email@example.com> wrote:
>> On Sat, Feb 11, 2012 at 7:39 PM, Kevin Gullikson
>> <firstname.lastname@example.org> wrote:
>> > Use full_output=True when you call leastq, and you will get a matrix
>> > other things). If you multiply that matrix by the standard deviation of
>> > 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
> 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.
> SciPy-User mailing list
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