AMCS 307 - Advanced Statistical Inference by Prof. Marco Scavino Teaching AMCS 241, 243, 245. Statistical inference in a wide range of problems at an advanced level. It covers the general theory of estimation, tests, and confidence intervals by deriving, in particular, the asymptotic properties of the maximum likelihood estimator and the likelihood ratio, Wald, and scores tests (and their generalizations), and the calculus of M- estimation.
AMCS 308 - Stochastic Numerics with Application in Simulation and Data Science by Prof. Raul Tempone Teaching Review of basic probability; Monte Carlo simulation; state-space models and time series; parameter estimation, prediction, and filtering; Markov chains and processes; stochastic control; Markov chain Monte Carlo. Examples from various engineering disciplines.
AMCS 336 - Fall 2022 - Numerical Methods for Stochastic Differential Equations by Prof. Raul Tempone Teaching Fall Semesters The goal of this course is to give basic knowledge of stochastic differential equations and their numerical solution, useful for scientific and engineering modeling, guided by some problems in applications in financial mathematics, material science, geophysical flow problems, turbulent diffusion, control theory, and Monte Carlo methods. We will discuss basic questions for numerical approximation of stochastic differential equations, for example: To determine the price of an option is it more efficient to solve the deterministic Black and Scholes partial differential equation or
Courses Teaching Fall Semesters AMCS 336 Numerical Methods for Stochastic Differential Equations by Prof. Raul Tempone Spring Semesters AMCS 308 Stochastic Numerics with Application in Simulation and Data Science by Prof. Raul Tempone Enrolled students can access courses material through KAUST's Blackboard via: https://blackboard.kaust.edu.sa
