Advances in Directional and Linear Statistics : A Festschrift for Sreenivasa Rao Jammalamadaka

Advances in Directional and Linear Statistics A Festschrift for Sreenivasa Rao Jammalamadaka

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.

Detalles Bibliográficos
Autor Corporativo: SpringerLink (-)
Otros Autores: Wells, Martin T. (-), SenGupta, Ashis
Formato: Libro electrónico
Idioma:Inglés
Publicado: Heidelberg : Physica-Verlag HD 2011.
Colección:Springer eBooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b32930185*spi
Tabla de Contenidos:
  • 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.

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