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Analysis of variance with general errors and grouped and non-grouped data: Some iterative algorithms

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  • Anido, Carmen
  • Rivero, Carlos
  • Valdés, Teófilo

Abstract

In this paper we consider some iterative estimation algorithms, which are valid to analyse the variance of data, which may be either non-grouped or grouped with different classification intervals. This situation appears, for instance, when data is collected from different sources and the grouping intervals differ from one source to another. The analysis of variance is carried out by means of general linear models, whose error terms may be general. An initial procedure in the line of the EM, although it does not necessarily agree with it, opens the paper and gives rise to a simplified version where we avoid the double iteration, which implicitly appears in the EM and, also, in the initial procedure mentioned above. The asymptotic stochastic properties of the resulting estimates have been investigated in depth and used to test ANOVA hypothesis.

Suggested Citation

  • Anido, Carmen & Rivero, Carlos & Valdés, Teófilo, 2008. "Analysis of variance with general errors and grouped and non-grouped data: Some iterative algorithms," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1544-1573, September.
    • Handle: RePEc:eee:jmvana:v:99:y:2008:i:8:p:1544-1573
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    References listed on IDEAS

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    1. An, Mark Yuying, 1998. "Logconcavity versus Logconvexity: A Complete Characterization," Journal of Economic Theory, Elsevier, vol. 80(2), pages 350-369, June.
    2. Michael Healy & Michael Westmacott, 1956. "Missing Values in Experiments Analysed on Automatic Computers," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 5(3), pages 203-206, November.
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