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Recolector de Ciencia Abierta, RECOLECTA
Bachelor thesis . 2020
License: CC BY NC SA
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Modelos no lineales de regresión

Authors: Cribeiro Ramallo, Jose Antonio;

Modelos no lineales de regresión

Abstract

[EN] In the following paper, we have revised the methods for the non linear regression models. We have studied the properties of consintency and the asymptotic distribution of the model estimator, on top of having presented a range of tools for the parameter inference. Furthermore, a simulation study has been taken where we have veri ed the multiple theorical properties of the estimators and the inferential methods exposed previosly, like the contrast statistics and con dence intervals, followed by a brief conlcusion of the results that have been obtained.

[ES] En este trabajo se ha hecho una revisión de los modelos no lineales. Se han estudiado las propiedades de consistencia y de distribución asintótica de los estimadores, y se han presentado los procedimientos para la inferencia sobre los parámetros del modelo. Además, se ha hecho un estudio por simulación en donde se han verificado varias propiedades teóricas de los estimadores y de los métodos inferenciales expuestos en la teoría, como intervalos de confianza y contrastes de hipótesis, acompañado de una breve conclusión de los resultados obtenidos

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green