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Robust analysis of variance with imprecise data: an ad hoc algorithm

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Rivero, Carlos and Valdés Sánchez, Teófilo (2011) Robust analysis of variance with imprecise data: an ad hoc algorithm. Environmental and ecological statistics, 18 (4). pp. 635-662. ISSN 1352-8505

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Official URL: http://link.springer.com/content/pdf/10.1007%2Fs10651-010-0155-7


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Abstract

We present an easy to implement algorithm, which is valid to analyse the variance of data under several robust conditions. Firstly, the observations may be precise or imprecise. Secondly, the error distributions may vary within the wide class of the strongly unimodal distributions, symmetrical or not. Thirdly, the variance of the errors is unknown. The algorithm starts by estimating the parameters of the ANOVA linear model. Then, the asymptotic covariance matrix of the effects is estimated. Finally, the algorithm uses this matrix estimate to test ANOVA hypotheses posed in terms of linear combinations of the effects.


Item Type:Article
Uncontrolled Keywords:Maximum-likelihood; linear-regression; censored-data; em algorithm; grouped data; consistency; errors; models; Computational hypothesis testing; Stochastic approximation; Robust ANOVA with precise and imprecise observations; Conditional imputation techniques; Consistency and asymptotic distributions
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:20176
Deposited On:28 Feb 2013 10:19
Last Modified:18 Jul 2018 11:02

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