First tentacle

oktopus includes the following:

• parameter estimation with built-in likelihood functions (Poisson, Gaussian, Multinomial, Laplace, and Multivariate Gaussian) using Maximum Likelihood Estimators
• parameter estimation with built-in and extern posterior distributions using Maximum A Posteriori Probability Estimators
• support for computation of uncertainties using Fisher Information Matrix
• L1 norm minimization with support for regularization terms
• support local and global optimizers (wrappers around scipy and scikit-optimize)
  oktopus has been applied in PSF photometry on data from NASA's Kepler and K2 missions. Check out http://pyke.keplerscience.org

See the full documentation at: https://keplergo.github.io/oktopus/index.html