Scipy stats.rv_continuous to find MLE from 2-dimensional data

Question

Referring to here , I would like to find the MLE of alpha and lam , given the following PDF

import scipy.stats as st
import numpy as np

class Weib(st.rv_continuous):

    def _pdf(self, data, alpha, lam):
        t = data[0]
        delta = data[1]
        fx = (alpha * lam * (t**(alpha-1)))**(delta) * np.exp(-lam * (t**alpha))
        return fx

    def _argcheck(self, alpha, lam):
        a = alpha > 0
        l = lam > 0 
        return (a & l)

And I tried

Weib_inst = Weib(name='Weib')
Samples = Weib_inst.rvs(alpha=1, lam=3, size = 1000)

And it says

'float' object is not subscriptable

Weib_inst._fitstart([[1,2],[2,4]]) also returns the same error message.

It seems this occurs because the data is not 1-dimensional, but I cannot find the way to bypass this.

Any help might be appreciated.

Answer 1

You may try to define _fitstart in your subclass. The framework assumes univariate distributions, however.