Nearest neighbor balanced block designs for autoregressive errors - Sorbonne Université
Journal Articles Metrika Year : 2021

Nearest neighbor balanced block designs for autoregressive errors

Abstract

In this paper we study the problem of finding neighbor optimal designs for a general correlation structure. We give universal optimality conditions for nearest-neighbor (NN) balanced block designs when observations on the same block are modeled by an autoregressive AR(m) process with arbitrary order m. The cases m=1,2 have been studied by Grondona and Cressie (Sankhyā Indian J Stat Ser A 55(2):267–284, 1993) for AR(2) and by Gill and Shukla (Biometrika 72(3):539–544, 1985a, Commun Stat Theory Methods 14(9):2181–2197, 1985b) and Kunert (Biometrika 74(4):717–724, 1987) for AR(1); we extend these results to the cases m≥3.
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Dates and versions

hal-01850854 , version 1 (27-07-2018)
hal-01850854 , version 2 (29-09-2018)
hal-01850854 , version 3 (08-09-2021)

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Mamadou Koné, Annick Valibouze. Nearest neighbor balanced block designs for autoregressive errors. Metrika, 2021, 84 (3), pp.281-312. ⟨10.1007/s00184-020-00770-6⟩. ⟨hal-01850854v3⟩
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