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Optimal Mixture Experiments

  • B.K. Sinha
  • N.K. Mandal
  • Manisha Pal
  • P. Das

Part of the Lecture Notes in Statistics book series (LNS, volume 1028)

Table of contents

  1. Front Matter
    Pages i-xix
  2. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 1-7
  3. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 9-21
  4. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 23-42
  5. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 43-61
  6. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 75-85
  7. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 87-109
  8. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 111-121
  9. B. K. Sinha, N. K. Mandal, Manisha Pal, P. Das
    Pages 149-159
  10. Back Matter
    Pages 201-209

About this book

Introduction

The book dwells mainly on the optimality aspects of mixture designs. As mixture models are a special case of regression models, a general discussion on regression designs has been presented, which includes topics like continuous designs, de la Garza phenomenon, Loewner order domination, Equivalence theorems for different optimality criteria and standard optimality results for single variable polynomial regression and multivariate linear and quadratic regression models. This is followed by a review of the available literature on estimation of parameters in mixture models. Based on recent research findings, the volume also introduces optimal mixture designs for estimation of optimum mixing proportions in different mixture models, which include Scheffé’s quadratic model, Darroch-Waller model, log- contrast model, mixture-amount models, random coefficient models and multi-response model.  Robust mixture designs and mixture designs in blocks have been also reviewed. Moreover, some applications of mixture designs in areas like agriculture, pharmaceutics and food and beverages have been presented. Familiarity with the basic concepts of design and analysis of experiments, along with the concept of optimality criteria are desirable prerequisites for a clear understanding of the book.  It is likely to be helpful to both theoreticians and practitioners working in the area of mixture experiments.

Keywords

Bayesian Analysis Design of Experiments Kiefer’s Equivalence Theorem Linear Models Loewner Order Domination Optimum Mixture Designs Regression Designs

Authors and affiliations

  • B.K. Sinha
    • 1
  • N.K. Mandal
    • 2
  • Manisha Pal
    • 3
  • P. Das
    • 4
  1. 1.Indian Statistical InstituteKolkataIndia
  2. 2.Department of StatisticsUniversity of CalcuttaKolkataIndia
  3. 3.Department of StatisticsUniversity of CalcuttaKolkataIndia
  4. 4.Department of StatisticsUniversity of KalyaniKalyani, NadiaIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-81-322-1786-2
  • Copyright Information Springer India 2014
  • Publisher Name Springer, New Delhi
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-81-322-1785-5
  • Online ISBN 978-81-322-1786-2
  • Series Print ISSN 0930-0325
  • Series Online ISSN 2197-7186
  • Buy this book on publisher's site
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