Elements of Large-Sample Theory (Springer Texts in Statistics)

Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)

Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics)

Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics)

Asymptotic Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)

A Course in Large Sample Theory (Chapman & Hall/CRC Texts in Statistical Science)

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Testing Statistical Hypotheses (Springer Texts in Statistics)

Deep Learning (Adaptive Computation and Machine Learning series)

Theory of Point Estimation (Springer Texts in Statistics)

Deep Learning with Python

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)