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| 현재위치 : 홈 > 도서목록 > 전체도서목록 > 통계 |
| Linear Model Theory: Univariate, Multivariate, and Mixed Models |
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| 지은이 |
: Muller |
| 발행일 |
: 2006 년 |
| ISBN |
: 9780471214885 |
| 정행가 |
: 40,000 원 |
| 페이지 |
: 410 페이지 |
| 판행수 |
: 1판 |
| 출판사 |
: Wiley |
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| 저자 및 역자 소개 |
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| 차례 |
Preface
PART I: MODELS AND EXAMPLES
1. Matrix Algebra for Linear Models
2. The General Linear Univariate Model
3. The General Linear Multivariate Model
4. Generalizations of the Multivariate Linear Model
5. The Linear Mixed Model
6. Choosing the Form of a Linear Model for Analysis
PART II: MULTIVARIATE DISTRIBUTION THEORY
7. General Theory of Multivariate Distributions
8. Scalar, vector, and Matrix Gaussian Distributions
9. Univariate Quadratic Forms
10. Multivariate Quadratic Forms
PART III: ESTIMATION IN LINEAR MODELS
11. Estimation for Univariate and Weighted Linear Models
12. Estimation for Multivariate Linear Models
13. Estimation for Generalizations of Multivariate Models
14. Estimation for Linear Mixed Models
PART IV: TESTS IN GAUSSIAN LINEAR MODELS
15. Tests for Univariate Linear Models
16. Tests for Multivariate Linear Models
17. Tests for Generalizations of Multivariate Linear Models
18. Tests for Linear Mixed Models
19. A Review of Multivariate and Univariate Linear Models
PART V: CHOOSING A SIMPLE SIZE IN GAUSSIAN LINEAR MODELS
20. Sample Size for Univariate Linear Model
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