Asymptotic Properties of Parameters in Nonlinear Regression Models

Pavel S. Knopov () and Arnold S. Korkhin ()
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Pavel S. Knopov: National Academy of Science of Ukraine
Arnold S. Korkhin: National Mining University

Chapter Chapter 2 in Regression Analysis Under A Priori Parameter Restrictions, 2012, pp 29-71 from Springer

Abstract: Abstract In this chapter, we investigate some regression models with unknown coefficients. We assume that the parametric set of unknown parameters is closed and, generally speaking, unbounded. The case of open sets is easier to study, because in most of the cases the asymptotic distribution of estimates is normal. This is not always true when the constraints are compact sets. Everywhere in the text we consider discrete time observations. It is known that the observation errors taken at different times can be dependent. We do not consider here the continuous time version, although in that case many statements listed below also take place.

Keywords: Nonlinear Regression Model; Discrete-time Observations; Continuous-time Version; Minimum Contrast Estimation; Dorogovtsev (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4614-0574-0_2

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DOI: 10.1007/978-1-4614-0574-0_2

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