Optimal covariate designs : theory and applications / Premadhis Das.
Publication details: New Delhi : Springer, 2015.Description: xvii, 221 pISBN:- 9788132224600
- 000SA.069 23 D229
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.069 D229 (Browse shelf(Opens below)) | Available | 136940 |
Browsing ISI Library, Kolkata shelves Close shelf browser (Hides shelf browser)
| No cover image available | No cover image available | |||||||
| 000SA.06=49 Y94 Proceedings of the 7th conference | 000SA.066 B743 Statistical information and likelihood | 000SA.067 Sh562 Quasi-least squares regression / | 000SA.069 D229 Optimal covariate designs : | 000SA.069 H668 Advanced analysis of variance / | 000SA.069 P877 High-dimensional covariance estimation / | 000SA.069 Sch316 Analysis of variance |
Includes bibliographical references and index.
1. Optimal Covariate Designs: Scope of the Monograph --
2. OCDs in Completely Randomized Design Set-Up --
3. OCDs in Randomized Block Design Set-Up --
4. OCDs in Balanced Incomplete Block Design Set-Up --
5. OCDs in Group Divisible Design Set-Up --
6. OCDs in Binary Proper Equireplicate Block Design Set-Up --
7. OCDs in Balanced Treatment Incomplete Block Design Set-Up --
8. Miscellaneous other Topics and Issues --
9. Applications of the Theory of OCDs.
This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for the construction of optimum designs using Hadamard matrices, the Kronecker product, Rao-Khatri product.
There are no comments on this title.
