[Numpy-discussion] Calculation of a hessian

[Kiko]

Hi all,

I am trying to calculate a Hessian. I am using numdifftools for this (
https://pypi.python.org/pypi/Numdifftools).

My question is, is it possible to make it using pure numpy?.

The actual code is like this:


*import numdifftools as nd*
*import numpy as np*

*def log_likelihood(params):*
*    sum1 = 0; sum2 = 0*
*    mu = params[0]; sigma = params[1]; xi = params[2]*
*    for z in data:*
*        x = 1 + xi * ((z-mu)/sigma)*
*        sum1 += np.log(x)*
*        sum2 += x**(-1.0/xi)*
*    return -((-len(data) * np.log(sigma)) - (1 + 1/xi)*sum1 - sum2) #
negated so we can use 'minimum'*

*kk = nd.Hessian(log_likelihood)*

Thanks in advance.
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