Other Useful References

In addition the main textbooks, the following references may be useful.

Related courses and lecture notes

• 18.657: High Dimensional Statistics MIT, Philippe Rigollet and Jan-Christian Hutter

• APC 550: Probability in High Dimension, Princeton, Ramon van Handel

• MATH 581: High Dimensional Probability and Statistical Learning, Washington, Dmitriy Drusvyatskiy

• Giraud, C. (2015). Introduction to High-Dimensional Statistics. CRC Press.

Mathematics background

• MATH 535: Mathematical Methods in Data Science, UW-Madison, Sebastien Roch.

• MATH 733/734: Theory of Probability I/II, UW-Madison, Sebastien Roch.

Statistics background

• Panaretos, V. M. (2016). Statistics for Mathematicians: A Rigorous First Course. Birkhauser/Springer.

• Wood, S. N. (2015). Core Statistics. CUP.

Classical statistical theory textbooks

• Bhattacharya, R. et al. (2016). A Course in Mathematical Statistics and Large Sample Theory. Springer.

• Lehmann, E. L. and Casella, G. (1998). Theory of point estimation. Springer.

• Lehmann, E. L. and Romano, J. P. (2005). Testing statistical hypotheses. Springer.

• Lehmann, E. L. (1998). Elements of large-sample theory. Springer.

• Shao, J. (2010). Mathematical statistics. Springer.

• Anderson, T. W. (2003). An introduction to multivariate statistical analysis. Wiley.