Abstract
It is simpler to understand the structure and the properties of a nonlinear model when the parameter ϑ is one-dimensional. Therefore, in this chapter the model
is considered. The parameter space is a bounded interval [a, b]. The observed vector y remains multidimensional, y ∈ R N The mapping
is assumed to be continuous, and twice continuously differentiable on (a, b). Further, the model is assumed to be regular, i.e.
for every ϑ ∈ (a, b).
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© 1993 Andrej Pázman
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Pázman, A. (1993). Univariate regression models. In: Nonlinear Statistical Models. Mathematics and Its Applications, vol 254. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-2450-0_4
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DOI: https://doi.org/10.1007/978-94-017-2450-0_4
Publisher Name: Springer, Dordrecht
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