Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer
biomechanists a wealth of data on healthy and pathological movement. To harness the power of …

This chapter discusses the innovations of additional flexible methods for modeling an
individual term in an additive model. It focuses on how we fit additive models. A general and …

This chapter explores statistical models—how to think about them, specify them, fit them,
and analyze them. Statistical models are simplified descriptions of data, usually constructed …

Background: Low-molecular-weight heparins may simplify the management of deep venous
thrombosis. A critical clinical issue is whether this more convenient therapy is as safe and …

There has been considerable interest in random projections, an approximate algorithm for
estimating distances between pairs of points in a high-dimensional vector space. Let A in R n …

Linear models and analysis of variance are popular. Many phenomena behave linearly and
have errors that are Gaussian. The chapter presents a class of models that is as tractable as …

… HASTIE Department of Statistics, Stanford University, California 94305-4065, USA hastie@…
Trevor Hastie was partially supported by grants from the National Science Foundation and …

We consider the problem of learning the structure of a pairwise graphical model over
continuous and discrete variables. We present a new pairwise model for graphical models with …

We introduce a technique for extending the classical method of linear discriminant analysis (LDA)
to data sets where the predictor variables are curves or functions. This procedure, …

Current work in elucidating relationships between diseases has largely been based on pre-existing
knowledge of disease genes. Consequently, these studies are limited in their …