Variance-balanced designs under interference for dependent observations

Martin, R. J.; Eccleston, J. A.

doi:10.1016/s0378-3758(02)00407-x

Cited by 9 publications

(2 citation statements)

References 19 publications

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“…Kunert et al [11] considered two related models for interference and have shown that optimal designs for one model can be obtained from optimal designs for the other model. Martin and Eccelston [14] have given variance balanced designs under interference and dependent observations. Santharam and Ponnuswamy [18] examined the optimality and efficiency of nearest neighbor balanced block designs when error follows Auto Regressive (AR), Moving Average (MA) or Auto Regressive Moving Average (ARMA) models.…”

Section: Introductionmentioning

confidence: 99%

Efficiency of Nearest Neighbour Balanced Block Designs for Second Order Correlated Error Structure

Kumar¹,

Santharam²

2017

IOSR JM

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Section: Introductionmentioning

confidence: 99%

Efficiency of Nearest Neighbour Balanced Block Designs for Second Order Correlated Error Structure

Kumar¹,

Santharam²

2017

IOSR JM

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“…We can construct efficient designs, like Kunert and Martin (2000), or we can make use of orthogonal arrays of type I, which achieve high efficiencies under any Φ p -criterion. 14 4 Efficiency of orthogonal arrays of type I An OA I (b, k, t, 2) uses sequences from equivalence class U 1 only and has a completely symmetric Martin and Eccelston (2004). Therefore, µ d1 = .…”

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confidence: 99%

Optimal designs for an interference model

Kunert

Mersmann

2011

Journal of Statistical Planning and Inference

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Kunert and Martin (2000) determined optimal and efficient block designs in a model for field trials with interference effects, for block sizes up to 4. In this paper we use Kushner's method (Kushner, 1997) of finding optimal approximate designs to extend the work of Kunert and Martin (2000) to optimal designs with five or more plots per block. We give an overall upper bound a * t,b,k for the trace of the information matrix of any design and show that an universally optimal approximate design will have all its sequences from merely four different equivalence classes. We further determine the efficiency of a binary type I orthogonal array under the general Φ p -criterion. We find that these designs achieve high efficiencies of more than 0.94.

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