Abstract
This chapter addresses the pure likelihood approach to model choice . The concepts of normalized , adjusted , relative , and profile likelihood are introduced. A relative likelihood approach for discriminating separate models is presented using an example. The concepts of computer simulations , the Monte Carlo method, Monte Carlo simulations , and bootstrapping are described. Linear and nonlinear regression models in the literature are used as illustrations. An example is presented to demonstrate the use of a likelihood dominance criterion (LDC) for model choice .
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Pereira, B., Pereira, C. (2016). Support and Simulation Methods. In: Model Choice in Nonnested Families. SpringerBriefs in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53736-7_4
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DOI: https://doi.org/10.1007/978-3-662-53736-7_4
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