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Matrices, Statistics and Big Data

Overview of attention for book
Cover of 'Matrices, Statistics and Big Data'

Table of Contents

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    Book Overview
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    Chapter 1 Further Properties of the Linear Sufficiency in the Partitioned Linear Model
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    Chapter 2 Hybrid Model for Recurrent Event Data
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    Chapter 3 A New Look at Combining Information from Stratum Submodels
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    Chapter 4 Ingram Olkin (1924–2016): An Appreciation for a People Person
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    Chapter 5 A Notion of Positive Definiteness for Arithmetical Functions
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    Chapter 6 Some Issues in Generalized Linear Modeling
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    Chapter 7 Orthogonal Block Structure and Uniformly Best Linear Unbiased Estimators
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    Chapter 8 Hadamard Matrices on Error Detection and Correction: Useful Links to BIBD
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    Chapter 9 Covariance Matrix Regularization for Banded Toeplitz Structure via Frobenius-Norm Discrepancy
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    Chapter 10 Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative Model
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    Chapter 11 High-Dimensional Regression Under Correlated Design: An Extensive Simulation Study
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    Chapter 12 An Efficient Estimation Strategy in Autoregressive Conditional Poisson Model with Applications to Hospital Emergency Department Data
Attention for Chapter 2: Hybrid Model for Recurrent Event Data
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Citations

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Chapter title
Hybrid Model for Recurrent Event Data
Chapter number 2
Book title
Matrices, Statistics and Big Data
Published by
Springer, Cham, June 2016
DOI 10.1007/978-3-030-17519-1_2
Book ISBNs
978-3-03-017518-4, 978-3-03-017519-1
Authors

Ivo Sousa-Ferreira, Ana Maria Abreu, Sousa-Ferreira, Ivo, Abreu, Ana Maria

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Lecturer 1 100%
Readers by discipline Count As %
Mathematics 1 100%

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