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Registro Completo |
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura; Embrapa Trigo. |
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Data corrente: |
18/08/1995 |
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Data da última atualização: |
15/09/1995 |
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Autoria: |
WILKINSON, G. N.; ECKERT, S. R.; HANCOCK, T. W.; MAYO, O. |
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Afiliação: |
Waite Agricultural Research Institute, University of Adelaide, Adelaide, Australia. |
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Título: |
Nearest neighbour (NN) analysis of field experiments. |
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Ano de publicação: |
1983 |
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Fonte/Imprenta: |
J. R. Statist. Soc. v.45, n.2, p.151-211, 1983. |
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Idioma: |
Inglês |
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Conteúdo: |
The paper is in two parts. Part I presents results of a Monte Carlo randomization study of Papadakis's covariance method of NN analysis which show that (i) a not-iterated Papadakis analysis tends to be conservatively biassed; (ii) iteration of the analysis as suggested by Bartlett (1978) leads to substantial positive bias in the treatment F ratio; (iii) the method is very inefficient when there are substantial trend effects in the data. A theoretical explanation of these results is given. Part II describes a new method of NN analysis discovered by the first author and developed in collaboration with the co-authors. The method is essentially a "moving-block" analogue of classical forms of analysis for "fixed"blocks (or rows, columns). It avoids the defects of Papadakis's method and leads to approximately unbiassed analyses. It is nearly always and often substantially more efficient on average than classical analyses of complete or incomplete block experiments, and also more efficient than standard analyses of Latin or lattice square designs if there are appreciable row X column interactions in the data. New criteria of design for NN balance are described. Validity of the new method under randomization is demonstrated empirically with Monte Carlo studies. |
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Palavras-Chave: |
Análise estatística experimental; Analysis of field experiments; Delineamento vizinho mais próximo; Intra-N analysis; Método de Monte Carlo; Método de Papadakis; Monte carlo; Nearest neighbour methods; NN analysis; Papadakis method; Papadakis's method; Randomization distributions. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02157naa a2200301 a 4500
001 1647092
005 1995-09-15
008 1983 bl --- 0-- u #d
100 1 $aWILKINSON, G. N.
245 $aNearest neighbour (NN) analysis of field experiments.
260 $c1983
520 $aThe paper is in two parts. Part I presents results of a Monte Carlo randomization study of Papadakis's covariance method of NN analysis which show that (i) a not-iterated Papadakis analysis tends to be conservatively biassed; (ii) iteration of the analysis as suggested by Bartlett (1978) leads to substantial positive bias in the treatment F ratio; (iii) the method is very inefficient when there are substantial trend effects in the data. A theoretical explanation of these results is given. Part II describes a new method of NN analysis discovered by the first author and developed in collaboration with the co-authors. The method is essentially a "moving-block" analogue of classical forms of analysis for "fixed"blocks (or rows, columns). It avoids the defects of Papadakis's method and leads to approximately unbiassed analyses. It is nearly always and often substantially more efficient on average than classical analyses of complete or incomplete block experiments, and also more efficient than standard analyses of Latin or lattice square designs if there are appreciable row X column interactions in the data. New criteria of design for NN balance are described. Validity of the new method under randomization is demonstrated empirically with Monte Carlo studies.
653 $aAnálise estatística experimental
653 $aAnalysis of field experiments
653 $aDelineamento vizinho mais próximo
653 $aIntra-N analysis
653 $aMétodo de Monte Carlo
653 $aMétodo de Papadakis
653 $aMonte carlo
653 $aNearest neighbour methods
653 $aNN analysis
653 $aPapadakis method
653 $aPapadakis's method
653 $aRandomization distributions
700 1 $aECKERT, S. R.
700 1 $aHANCOCK, T. W.
700 1 $aMAYO, O.
773 $tJ. R. Statist. Soc.$gv.45, n.2, p.151-211, 1983.
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Registro original: |
Embrapa Mandioca e Fruticultura (CNPMF) |
