University of California, SC

Dissertation

Advancement: A latent space approach for exchangeable multinetwork data by J. Sosa

Dissertation: A latent space approach for cognitive social structures modeling and graphical record linkage by J. Sosa

First Year Exam

Summary: Applied Mathematics

Summary: Bayesian Inference

Summary: Classical Inference

Summary: Intermediate Bayesian Modeling

Summary: Linear Statistical Models

Summary: Probability

The hierarchical normal model in a linear regression setting by J. Sosa

Probability

DeGroot, M. H., & Schervish, M. J. (2012). Probability and Statistics (4th ed.). Boston: Pearson

Kadane, J. B. (2011). Principles of Uncertainty. Chapman & Hall/CRC

Probability Basics

Probability Theory Summary

Classical Inference

Casella, G., & Berger, R. L. (2002). Statistical Inference (2nd ed.). Duxbury Press

The Solutions Manual for Statistical Inference, Second Edition

Lecture notes by D. Draper

Code by D. Draper

Fisher Information and Cramér-Rao Bound by S. Zheng

Take-home exam 1 by J. Sosa

Take-home exam 2 by J. Sosa

Take-home exam 3 by J. Sosa

Take-home exam 4 by J. Sosa

Bayesian Inference

Robert, C. P. (2007). The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (2nd ed.). Springer

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis (3rd ed.). CRC Press

Hoff, P. D. (2009). A First Course in Bayesian Statistical Methods. Springer

Take-home exam 1 by J. Sosa

Take-home exam 2 by J. Sosa

Take-home exam 3 by J. Sosa

Take-home exam 4 by J. Sosa

Intermediate Bayesian Modeling

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis (3rd ed.). CRC Press

Hoff, P. D. (2009). A First Course in Bayesian Statistical Methods. Springer

Solutions to some exercises from BDA 3

Lecture notes by B. Sansó

Lecture notes by M. I. Jordan

Quiz 1 by J. Sosa

Quiz 2 by J. Sosa

Midterm by J. Sosa

Applied Mathematics

Riley, K. F., Hobson, M. P., & Bence, S. J. (2006). Mathematical Methods for Physics and Engineering: A Comprehensive Guide (3rd ed.). Cambridge University Press

Mathematical Methods for Physics and Engineering - Solutions odds

Mathematical Methods for Physics and Engineering - Solutions evens

Time Series

Prado, R., West, M., & Krystal, A. (2021). Time Series: Modeling, Computation, and Inference. Chapman & Hall/CRC Press

West, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer-Verlag

Petris, G., Petrone, S., & Campagnoli, P. (2009). Dynamic Linear Models with R. Springer

Shumway, R. H., & Stoffer, D. S. (2017). Time Series Analysis and Its Applications with R Examples (4th ed.). Springer

The Matrix Cookbook

Multivariate Normal Distribution

Lecture notes by R. Prado

Take-home exam 1 by J. Sosa

Take-home exam 2 by J. Sosa

Take-home exam 3 by J. Sosa

Bayesian Nonparametric Methods

Müller, P., & Rodriguez, A. (2012). Nonparametric Bayesian Inference. Lecture Notes–Monograph Series, Vol. XYZ. Institute of Mathematical Statistics, Beachwood, Ohio, USA.

Lecture Notes on Bayesian Nonparametrics by Peter Orbanz

Lecture notes by A. Rodríguez

Lecture notes by T. Kottas

Homework 1 by J. Sosa

Homework 2 by J. Sosa

Project - Variational Algorithm for Dirichlet Process Mixtures

Spatial Statistics

Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). Chapman and Hall/CRC Press

Lecture notes by B. Sansó

Lecture notes by S. Banerjee

Homework 1 by J. Sosa

Homework 2 by J. Sosa

Homework 3 by J. Sosa

Homework 4 by J. Sosa

Homework 5 by J. Sosa

Homework 6 by J. Sosa

Linear Statistical Models

Christensen, R. (2011). Plane Answers to Complex Questions: The Theory of Linear Models (4th ed.). New York: Springer

Faraway, J. J. (2005). Linear Models with R. Boca Raton, FL: Chapman & Hall/CRC

Harville, D. A. (2008). Matrix Algebra from a Statistician's Perspective. New York: Springer

Some Linear Algebra

Lecture notes by A. Rodríguez

Homework 1 by J. Sosa

Homework 2 by J. Sosa

Homework 3 by J. Sosa

Project - Boston Data by J. Sosa

Stochastic Processes

Ross, S. M. (2014). Introduction to Stochastic Processes (2nd ed.). New York: Wiley

Durrett, R. (2016). Essentials of Stochastic Processes (3rd ed.). New York: Springer

Grimmett, G., & Stirzaker, D. (2020). Probability and Random Processes (4th ed.). Oxford: Oxford University Press

Lecture notes by T. Kottas

Homework 1 by J. Sosa

Homework 2 by J. Sosa

Homework 3 by J. Sosa

Project - Hierarchical Gaussian process mixtures for regression by J. Sosa

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