E-Book, Englisch, 321 Seiten, eBook
Wells / SenGupta Advances in Directional and Linear Statistics
1. Auflage 2010
ISBN: 978-3-7908-2628-9
Verlag: Physica
Format: PDF
Kopierschutz: 1 - PDF Watermark
A Festschrift for Sreenivasa Rao Jammalamadaka
E-Book, Englisch, 321 Seiten, eBook
ISBN: 978-3-7908-2628-9
Verlag: Physica
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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.