This volume presents selections of Peter J. Bickel's major papers, along with comments on their novelty and impact on the subsequent development of statistics as a discipline. Each of the eight parts concerns a particular area of research and provides new commentary by experts in the area. The parts range from Rank-Based Nonparametrics to Function Estimation and Bootstrap Resampling. Peter's amazing career encompasses the majority of statistical developments in the last half-century or about about half of the entire history of the systematic development of statistics. This volume shares insights on these exciting statistical developments with future generations of statisticians. The compilation of supporting material about Peter's life and work help readers understand the environment under which his research was conducted. The material will also inspire readers in their own research-based pursuits. This volume includes new photos of Peter Bickel, his biography, publication list, and a list of his students. These give the reader a more complete picture of Peter Bickel as a teacher, a friend, a colleague, and a family man.

Collected papers of Peter J. Bickel all in one volume Contains complete publication list, Ph.D students and photos of Bickel New commentary by statisticians from around the world Includes supplementary material: sn.pub/extras

Autorentext

Since obtaining his Ph.D. degree at the age of 22, Peter Bickel's fifty years of distinguished work spans the revolution of scientific computing and data collection, from vacuum tubes for processing and small experimental data to today's supercomputing and automated massive data scanning. The evolution of scientific computing and data collection has a profound impact on statistical thinking, methodological developments, and theoretical studies, thus creating evolving frontiers of statistics.

Inhalt

Foreword by Peter J. Bickel.- Preface.- Biography.- Publications.- Ph.D. Students.- Photos.- Rank-Based Nonparametrics.- Robust Statistics.- Asymptotic Theory.- Functional Estimation.- Adaptive Estimation.- Bootstrap Resampling.- High-Dimensional Statistics.- Miscellaneous.