M

mcmc

gemlib provides Python modules for implementing epidemic models.

API reference: https://gem-epidemics.gitlab.io/gemlib

This thesis addresses the challenges of modernizing Germany's power grid, quantifying risks posed by renewable energy in terms of grid stability. Stability measures are defined. Variability is quantified by fitting Gaussian Mixture Models (GMM) Principal on the Component Analysis (PCA) which is used for dimensionality reduction. Using MCMC techniques find low-probability patterns linked to blackouts and desynchronization.

MULTIGRIS ("mgris") is a Bayesian multi-dimensional grid search using PyMC to extract the posterior distributions of primary grid parameters and predict unobserved parameters/observables.

Stochastic superpositional posterior repartitioning used in conjunction with Bayesian inference engines such as PolyChord and MultiNest.

Codes will be uploaded here that are useful to study cosmology

Implementation of a Metropolis-within-Gibbs sampler in Python.

Trolley implements Bayesian statistical algorithms like Markov Chain Monte Carlo (MCMC).

A analysis & post-processing framework written in Python for the KATRIN experiment.

Uses NumPy, SciPy, Matplotlib, LMFit, PyROOT, emcee & others to easily produce plots from existing data sets.