Jalmar M. F. Carrasco, S. Ferrari, R. Arellano-Valle
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引用次数: 0
Abstract
. This paper deals with beta regression models with a covariate that is not directly observed; instead, it is replaced by a surrogate covariate that underpredicts its actual value. We propose a multiplicative errors-in-variables model tailored for this situation and develop calibration regression and pseudo-likelihood-based inference for the unknown parameters. The impact of ignoring the measurement error and the performance of the inference methods are evaluated through simulations and a real data illustration.
期刊介绍:
The Brazilian Journal of Probability and Statistics aims to publish high quality research papers in applied probability, applied statistics, computational statistics, mathematical statistics, probability theory and stochastic processes.
More specifically, the following types of contributions will be considered:
(i) Original articles dealing with methodological developments, comparison of competing techniques or their computational aspects.
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(iv) Survey articles containing a thorough coverage of topics of broad interest to probability and statistics. The journal will occasionally publish book reviews, invited papers and essays on the teaching of statistics.