Advances in Directional and Linear Statistics (eBook, PDF)

A Festschrift for Sreenivasa Rao Jammalamadaka
Redaktion: Wells, Martin T.; Sengupta, Ashis

• Format: PDF

Produktbeschreibung

The present volume consists of papers written by students, colleagues and collaborators of Sreenivasa Rao Jammalamadaka from various countries, and covers a variety of research topics which he enjoys and contributed immensely to.

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Produktdetails

• Verlag: Physica-Verlag HD
• Seitenzahl: 321
• Erscheinungstermin: 4. November 2010
• Englisch
• ISBN-13: 9783790826289
• Artikelnr.: 37398554

Autorenporträt

Professor Sreenivasa Rao Jammalamadaka, formerly known as J. S. Rao and affectionately known to most of us as JS, was born on December 7, 1944, at Munipalle, India. Being under-aged for engineering studies was a blessing in disguise, and he was among the first batch of students selected for the Bachelor of Statistics (B. Stat.) degree at the Indian Statistical Institute (ISI), Kolkata. He received his Masters and Ph.D. degrees also from the ISI, and has the distinction of being the first B.Stat.-M.Stat.-Ph.D. of the ISI. He received his education from such legendary figures as Professors P. C. Mahalanobis, J. B. S. Haldane, C. R. Rao, and D. Basu among others, and worked with Professor C.R. Rao for his Ph.D. (1969) on a then newly emerging area, Directional Data Analysis. JS moved to the USA in 1969 and was a faculty member at the Indiana University and then at the University of Wisconsin, Madison, before he moved to the University of California, Santa Barbara (UCSB) in 1976, where he has remained since then. At UCSB he played a leading role in creating the new Department of Statistics and Applied Probability and was its first Chairman. He has been a prodigious mentor to the graduate students in that department, having provided guidance to as many of 35 Ph.D. students, at the last count. Throughout his career, JS has been generous to his colleagues in India, inviting them to the U.S. and spending many of his sabbaticals helping Universities in India as well as in other countries. JS has published extensively in leading international journals. His research work spans a wide spectrum which includes: Goodness-of-Fit tests, Linear Models, Non-parametric and Semi-parametric inference, Bayesian analysis, Reliability, Spacings statistics, and most notably, Directional Data Analysis. He has written several books, both for undergraduate students as well as for advanced researchers. He has collaborated with a large number of researchers from around the world in general, and from India in particular. A Fellow of both the ASA and the IMS among other professional organizations, he has served the cause of statistics at many national and international levels, including that of the President of the International Indian Statistical Association.

Inhaltsangabe

Models for Axial Data.- Asymptotic Behavior of the Universally Consistent Conditional U-Statistics for Nonstationary and Absolutely Regular Processes.- Regression Models with STARMA Errors - An Application to the Study of Temperature Variations in the Antarctic Peninsula.- The Generalized von Mises-Fisher Distribution.- A New Nonparametric Test of Symmetry.- A Semiparametric Bayesian Method of Clustering Genes Using Time-Series of Expression Profiles.- On Implementation of the Markov Chain Monte Carlo Stochastic Approximation Algorithm.- Stochastic Comparisons of Spacings from Heterogeneous Samples.- The Distributions of the Peak to Average and Peak to Sum Ratios under Exponentiality.- Least Square Estimation for Regression Parameters under Lost Association.- On Tests of Fit Based on Grouped Data.- Innovation Processes in Logically Constrained Time Series.- Laws of Large Numbers and Nearest Neighbor Distances.- Nonparametric and Probabilistic Classification using NN-balls with Environmental and Remote Sensing Applications.- Probabilistic Recurrence Relations.- On Some Inequalities of Chernoff-Borovkov-Utev Type for Circular Distributions.- Revisiting Local Asymptotic Normality (LAN) and Passing on to Local Asymptotic Mixed Normality (LAMN) and Local Asymptotic Quadratic (LAQ) Experiments.- Long Range Dependence in Third Order for Non-Gaussian Time Series.- Graphical Models for Clustered Binary and Continuous Responses.