Abstract
This chapter reviews fundamental ideas from linear model theory for dealing with dependent or heteroscedastic data when the nature of the dependence or heteroscedasticity is known. It then introduces general ideas for estimating dependence or heteroscedasticity when their exact natures are unknown. Most of the book, after this chapter, consists of applications of these ideas to specific models.
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Christensen, R. (2019). Covariance Parameter Estimation. In: Advanced Linear Modeling. Springer Texts in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-29164-8_4
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DOI: https://doi.org/10.1007/978-3-030-29164-8_4
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