Course Description
The philosophical and theoretical basis of Bayesian analysis, with applications in civil engineering, environmental engineering, and the environmental sciences. Readily available software will be used throughout the course. Specific applications will depend on the needs of the students in the course.
Athena Title
Bayesian Engr Environ Sci
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
To develop an understanding of the philosophical and theoretical basis for Bayesian analysis To develop programming skills needed to perform Bayesian analysis using commonly available software To apply Bayesian methods to civil engineering, environmental engineering, and environmental sciences data To develop an ability to read, comprehend, and contribute to the literature in environmental engineering and sciences using Bayesian methods.
Topical Outline
Philosophical basis for Bayesian analysis Theoretical basis for Bayesian analysis Review of basic probability theory Bayes’s Rule Exact analysis of binomial models Linear and nonlinear regression problems Markov Chain Monte Carlo Application to temperature effects on structural behavior Application to noise parameters selection for the Kalman filter Application to particulate matter concentration Bayesian Spectral Density Approach Random vibration analysis Optimal sensor placement Application to structural behavior during hurricanes Application to hydrologic jump Linear optimization problem Application to model updating with unmeasured earthquake ground motion Model updating using eigenvalue – eigenvector measurements Application to structural health monitoring Bayesian model class selection Labs Basics of R, JAGS, and Stan software packages (3 weeks) Linear models Multivariate models Overfitting, regularization, and information criteria interactions Markov Chain Monte Carlo Big entropy and the generalized linear model Counting and classification Multilevel models