Abstract
Mathematically, parameters are the unknown quantities θ in the likelihood function, L(θ), whose values \( \hat \theta \) at the optimum are regarded as giving the best fit of the model to the data. There is an unlimited number of ways of writing the same model in terms of different sets of parameters. But the reasons for a particular parametrization of θ are not generally discussed in statistical texts.
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© 1990 Springer-Verlag New York, Inc.
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Ross, G.J.S. (1990). Transformations of Parameters. In: Nonlinear Estimation. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3412-8_2
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DOI: https://doi.org/10.1007/978-1-4612-3412-8_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-8001-9
Online ISBN: 978-1-4612-3412-8
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