Journal ArticleDOI
D-Optimal Designs for Covariate Parameters in Block Design Set Up
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In this article, the problem of finding D-optimal design for the estimation of covariate parameters and the treatment and block contrasts in a block design set up in the presence of non-stochastic controllable covariates was considered.Abstract:
The problem considered is that of finding D-optimal design for the estimation of covariate parameters and the treatment and block contrasts in a block design set up in the presence of non stochastic controllable covariates, when N = 2(mod 4), N being the total number of observations. It is clear that when N ≠ 0 (mod 4), it is not possible to find designs attaining minimum variance for the estimated covariate parameters. Conditions for D-optimum designs for the estimation of covariate parameters were established when each of the covariates belongs to the interval [−1, 1]. Some constructions of D-optimal design have been provided for symmetric balanced incomplete block design (SBIBD) with parameters b = v, r = k = v − 1, λ =v − 2 when k = 2 (mod 4) and b is an odd integer.read more
Citations
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Optimum covariate designs in a binary proper equi-replicate block design set-up
TL;DR: The problem of finding the optimum covariate design (OCD) for the estimation of covariate parameters in a binary proper equi-replicate block (BPEB) design model with covariates, which cover a large class of designs in common use, is considered.
Journal ArticleDOI
D-Optimal Designs for Covariate Models
TL;DR: In this article, an alternative upper bound to the determinant of the information matrix has been found through completely symmetric C-matrices for the regression coefficients; this upper bound includes the upper bound given in Dey and Mukerjee (2006) obtained through diagonal C-Matrices.
Journal ArticleDOI
Optimum Design for Estimation of Regression Parameters in Multi-Factor Set-Up
Ganesh Dutta,Premadhis Das +1 more
TL;DR: In this paper, the authors extended these results and proposed an extended mixed orthogonal array (EMOA) for the multi-factor set-up where the factorial effects involving at most t (≤m) factors are orthogonally estimable.
Journal ArticleDOI
Optimum designs for estimation of regression parameters in a balanced treatment incomplete block design set-up
Ganesh Dutta,Premadhis Das +1 more
TL;DR: In this paper, optimum covariate designs have been considered for the set-up of the balanced treatment incomplete block (BTIB) designs, which form an important class of test-control designs.
Journal ArticleDOI
A Review on Optimum Covariate Designs
TL;DR: In this paper, a short review of the present developments in this connection is presented, where the covariate effects were estimated with global optimality and a series of different design set-ups and proposed optimum covariate designs were considered.
References
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Journal ArticleDOI
Optimum covariate designs in partially balanced incomplete block (PBIB) design set-ups
TL;DR: In this article, the authors considered the situation where there is some flexibility for selection in the values of the covariates and proposed a more complex set-up of different partially balanced incomplete block (PBIB) designs, which are popular among practitioners.
Journal ArticleDOI
Optimum covariate designs in split-plot and strip-plot design set-ups
TL;DR: In this article, the problem of finding optimum covariate designs for estimation of covariate parameters in standard split-plot and strip-plot design set-ups with the levels of the whole-plot factor in r randomised blocks is considered.