  Jayanta Kumar Ghosh is one of the most extraordinary professors in the field
of Statistics. His research in numerous areas, especially asymptotics, has been
groundbreaking, influential throughout the world, and widely recognized through
awards and other honors. His leadership in Statistics as Director of the Indian
Statistical Institute and President of the International Statistical Institute,
among other eminent positions, has been likewise outstanding. In recognition of
Jayanta's enormous impact, this volume is an effort to honor him by drawing
together contributions to the main areas in which he has worked and continues
to work. The papers naturally fall into five categories. First, sequential
estimation was Jayanta's starting point. Thus, beginning with that topic, there
are two papers, one classical by Hall and Ding leading to a variant on
p-values, and one Bayesian by Berger and Sun extending reference priors to
stopping time problems. Second, there are five papers in the general area of
prior specification. Much of Jayanta's earlier work involved group families as
does Sweeting's paper here for instance. There are also two papers dwelling on
the link between fuzzy sets and priors, by Meeden and by Delampady and Angers.
Equally daring is the work by Mukerjee with data dependent priors and the
pleasing confluence of several prior selection criteria found by Ghosh, Santra
and Kim. Jayanta himself studied a variety of prior selection criteria
including probability matching priors and reference priors.
