Matrices, Statistics and Big Data: Selected Contributions from Iwms 2016 (Paperback, 2019)

Preface (S. Ejaz Ahmed, Francisco Carvalho, Simo Puntanen).- Further properties of the linear sufficiency in the partitioned linear model (Augustyn Markiewicz, Simo Puntanen).- Hybrid model for recurrent event data (Ivo Sousa-Ferreira, Ana Maria Abreu).- A new look at combining information from stratum submodels (Radosław Kala).- Ingram Olkin (1924?2016): An appreciation for a people person (Simo Puntanen, George P. H. Styan).- A notion of positive definiteness for arithmetical functions (Mika Mattila, Pentti Haukkanen).- Some issues in generalized linear modeling (Alan Agresti).- Orthogonal block structure and uniformly best linear unbiased estimators (Sandra S. Ferreira, Dario Ferreira, Celia Nunes, Francisco Carvalho, Joao Tiago Mexia).- Hadamard matrices on error detection and correction: Useful links to BIBD (Carla Francisco, Teresa A. Oliveira, Amilcar Oliveira, Francisco Carvalho).- Covariance matrix regularization for banded Toeplitz-structure via Frobenius-norm discrepancy (Xiangzhao Cui, Zhenyang Li, Jine Zhao, Defei Zhang, Jianxin Pan).- Penalized relative error estimation of a partially functional linear multiplicative model (Tao Zhang, Yuan Huang, Qingzhao Zhang, Shuangge Ma, S. Ejaz Ahmed).- High-dimensional regression under correlated design: An extensive simulation study (S. Ejaz Ahmed, Hwanwoo Kim, Gokhan Yıldırım and Bahadır Yuzba?ı).- An efficient estimation strategy in autoregressive conditional Poisson model with applications to hospital emergency department data (S. Ejaz Ahmed, Khalifa Es-Sebaiy, Abdulkadir Hussein, Idir Ouassou, Anne Snowdon).