The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

This lively book lays out a methodology of confidence distributions and puts them through
their paces. Among other merits they lead to optimal combinations of confidence from …

This paper proposes a method to address the longstanding problem of lack of monotonicity
in estimation of conditional and structural quantile functions, also known as the quantile …

Vector space models for symbolic processing that encode symbols by random vectors have
been proposed in cognitive science and connectionist communities under the names Vector …

This book is mainly about goodness-of-fit testing, particularly about tests for the one-and the
two-and K-sample problems. In the one-sample problem we need to test the hypothesis that …

To navigate in new environments, an animal must be able to keep track of its position while
simultaneously creating and updating an internal map of features in the environment, a …

In some applications (eg, in cosmology and economics), the regression E [Z| x] is not
adequate to represent the association between a predictor x and a response Z because of …

Distributed vector representations are a key bridging point between connectionist and
symbolic representations of cognition. It is unclear how uncertainty should be modelled in …

We consider a two‐component mixture model where one component distribution is known
while the mixing proportion and the other component distribution are unknown. These kinds …

Mixtures of Beta densities have led to different methods of density estimation for univariate
data assumed to have compact support. One such method relies on Bernstein polynomials …