Assignment#4 Predictive Modeling

Resolución ejercicio de calculo variacional

The Metropolis–Hastings (MH) algorithm is a Markov Chain Monte Carlo (MCMC) technique widely used to sample from complex probability distributions. Specifically, this report employs a Random Walk Metropolis–Hastings approach, in which proposed updates to the parameter values are generated by random perturbations around the current state. This algorithm enables efficient approximation the target distribution by drawing a series of dependent samples.