16. \(\chi^2\), Maximum Likelihood and Minimizing

16.1. \(\chi^2\) & Maximum Likelihood

scipy.optimize.curve_fit

• https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html#scipy.optimize.curve_fit

• Uses non-linear least squares

scipy.optimize.minimize

• https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html#scipy.optimize.minimize

• Many numerical methods

16.2. Emcee

https://emcee.readthedocs.io/en/stable/tutorials/line/

But include how a uniform distribution in slope is not uninformed, https://jakevdp.github.io/blog/2014/06/14/frequentism-and-bayesianism-4-bayesian-in-python/.

16.3. Further Reading

• https://jakevdp.github.io/blog/2014/06/14/frequentism-and-bayesianism-4-bayesian-in-python/

• https://emcee.readthedocs.io/en/stable/tutorials/line/