A substantial school in the philosophy of science identifies Bayesian inference with inductive
inference and even rationality as such, and seems to be strengthened by the rise and …

Critical research questions in the study of addictive behaviors concern how these behaviors
change over time: either as the result of intervention or in naturalistic settings. The …

This first chapter formulates the objectives of compressive sensing. It introduces the
standard compressive problem studied throughout the book and reveals its ubiquity in many …

Working under local differential privacy-a model of privacy in which data remains private
even from the statistician or learner-we study the tradeoff between privacy guarantees and …

Summary Background Anti-NMDA receptor (NMDAR) encephalitis is an autoimmune
disorder in which the use of immunotherapy and the long-term outcome have not been …

Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

A new edition of the definitive guide to logistic regression modeling for health science and
other applications This thoroughly expanded Third Edition provides an easily accessible …

It is common practice in statistical data analysis to perform data-driven variable selection
and derive statistical inference from the resulting model. Such inference enjoys none of the …

Supplementary material for Least squares after model selection in high-dimensional sparse
models. The online supplemental article 2 contains a finite sample results for the estimation …

We consider the generic problem of performing sequential Bayesian inference in a state
space model with observation process y, state process x and fixed parameter θ. An idealized …