Abstract
In this article, we extended the classic Box–Cox transformation to spatial linear models. For a comparative study, the proposed models were applied to a real data set of Chinese population growth and economic development with three different structures: no spatial correction, conditional autoregressive and simultaneous autoregressive. Maximal likelihood method was used to estimate the Box–Cox parameter λ and other parameters in the models. The residuals of the models were analyzed through Moran’s I and Geary’s c.
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Lai, D. Box–Cox transformation for spatial linear models: a study on lattice data. Stat Papers 51, 853–864 (2010). https://doi.org/10.1007/s00362-008-0178-4
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DOI: https://doi.org/10.1007/s00362-008-0178-4