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1.

電子ブック
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1. Large Sample Techniques for Statistics. 1
by Jiming Jiang
出版情報: New York, NY : Springer Science+Business Media, LLC, 2010
シリーズ名: Springer Texts in Statistics ; 0
オンライン: http://dx.doi.org/10.1007/978-1-4419-6827-2
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2.

電子ブック
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2. Linear and Generalized Linear Mixed Models and Their Applications
by Jiming Jiang
出版情報: New York, NY : Springer Science + Business Media, LLC, 2007
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-0-387-47946-0
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3.

電子ブック
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3. Linear and Generalized Linear Mixed Models and Their Applications. 2nd ed. 2021
by Jiming Jiang, Thuan Nguyen
出版情報: New York, NY : Springer New York : Imprint: Springer, 2021
シリーズ名: Springer Series in Statistics ;
オンライン: https://doi.org/10.1007/978-1-0716-1282-8
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目次情報: 続きを見る
1. Linear Mixed Models: Part I
2. Linear Mixed Models: Part II
3. Generalized Linear Mixed Models: Part I
4. Generalized Linear Mixed Models: Part II
1. Linear Mixed Models: Part I
2. Linear Mixed Models: Part II
3. Generalized Linear Mixed Models: Part I
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電子ブック
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4. Large Sample Techniques for Statistics. 2nd ed. 2022
by Jiming Jiang
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2022
シリーズ名: Springer Texts in Statistics ;
オンライン: https://doi.org/10.1007/978-3-030-91695-4
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目次情報: 続きを見る
Chapter 1. The -δ Arguments
Chapter 2. Modes of Convergence
Chapter 3. Big O, Small o, and the Unspecified c
Chapter 4. Asymptotic Expansions
Chapter 5. Inequalities
Chapter 6. Sums of Independent Random Variables
Chapter 7. Empirical Processes
Chapter 8. Martingales
Chapter 9. Time and Spatial Series
Chapter 10. Stochastic Processes
Chapter 11. Nonparametric Statistics
Chapter 12. Mixed Effects Models
Chapter 13. Small-Area Estimation
Chapter 14. Jackknife and Bootstrap
Chapter 15. Markov-Chain Monte Carlo
Chapter 16. Random Matrix Theory
Chapter 1. The -δ Arguments
Chapter 2. Modes of Convergence
Chapter 3. Big O, Small o, and the Unspecified c