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Matrices, statistics and big data = ...
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Workshop on the Preservation of Stability under Discretization ((2001 :)
Matrices, statistics and big data = selected contributions from IWMS 2016 /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Matrices, statistics and big data/ edited by S. Ejaz Ahmed, Francisco Carvalho, Simo Puntanen.
Reminder of title:
selected contributions from IWMS 2016 /
remainder title:
IWMS 2016
other author:
Ahmed, S. Ejaz.
corporate name:
Workshop on the Preservation of Stability under Discretization
Published:
Cham :Springer International Publishing : : 2019.,
Description:
xii, 190 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Matrices - Congresses. -
Online resource:
https://doi.org/10.1007/978-3-030-17519-1
ISBN:
9783030175191
Matrices, statistics and big data = selected contributions from IWMS 2016 /
Matrices, statistics and big data
selected contributions from IWMS 2016 /[electronic resource] :IWMS 2016edited by S. Ejaz Ahmed, Francisco Carvalho, Simo Puntanen. - Cham :Springer International Publishing :2019. - xii, 190 p. :ill. (some col.), digital ;24 cm. - Contributions to statistics,1431-1968. - Contributions to statistics..
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, João 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, Gökhan Yıldırım and Bahadır Yüzbaşı) -- 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)
This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data. The contributions were originally presented at the 25th International Workshop on Matrices and Statistics (IWMS 2016), held in Funchal (Madeira), Portugal on June 6-9, 2016. The IWMS workshop series brings together statisticians, computer scientists, data scientists and mathematicians, helping them better understand each other's tools, and fostering new collaborations at the interface of matrix theory and statistics.
ISBN: 9783030175191
Standard No.: 10.1007/978-3-030-17519-1doiSubjects--Topical Terms:
527694
Matrices
--Congresses.
LC Class. No.: QA188
Dewey Class. No.: 519.5
Matrices, statistics and big data = selected contributions from IWMS 2016 /
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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, João 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, Gökhan Yıldırım and Bahadır Yüzbaşı) -- 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)
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This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data. The contributions were originally presented at the 25th International Workshop on Matrices and Statistics (IWMS 2016), held in Funchal (Madeira), Portugal on June 6-9, 2016. The IWMS workshop series brings together statisticians, computer scientists, data scientists and mathematicians, helping them better understand each other's tools, and fostering new collaborations at the interface of matrix theory and statistics.
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Mathematics and Statistics (Springer-11649)
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