Optimal Designs for Covariates’ Models with Structured Intercept Parameter

  • Erkki P. Liski
  • Nripes K. Mandal
  • Kirti R. Shah
  • Bikas K. Sinha
Part of the Lecture Notes in Statistics book series (LNS, volume 163)


Model(s): Discrete design models with controllable covariates or multifactor linear regression models with structured intercept parameter Experimental domains: Binary set-up for discrete designs and T = [−1,1] for covariates Optimality criteria: Most efficient estimation of treatment parameters and covariate parameters Major tools: Mutually orthogonal latin squares and Hadamard matrices Optimality results: Optimal designs under CRD, RBD and BIBD set-up Thrust: Combinatorial optimization in terms of orthogonality (i) between factors versus blocks and treatments and also (ii) within the factors with levels ±1


Orthogonal Array Information Matrix Randomize Block Design Incidence Matrix Cyclical Permutation 
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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Erkki P. Liski
    • 2
  • Nripes K. Mandal
    • 1
  • Kirti R. Shah
    • 4
  • Bikas K. Sinha
    • 3
  1. 1.Department of StatisticsCalcutta UniversityCalcuttaIndia
  2. 2.Department of Mathematics, Statistics, and PhilosophyUniversity of TampereTampereFinland
  3. 3.Stat-Math DivisonIndian Statistical InstituteCalcuttaIndia
  4. 4.Department of Statistics and Actuarial ScienceUniversity of WaterlooWaterlooCanada

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