Ahmad, Basheer:Direct Likelihood Approximations for Generalized Linear Mixed Models
- Livres de poche 2010, ISBN: 9783639286939
[ED: Softcover], [PU: VDM Verlag Dr. Müller], It is a standard approach to consider the maximum likelihood estimation procedure for the estimation of parameters in statistical modelling. … Plus…
[ED: Softcover], [PU: VDM Verlag Dr. Müller], It is a standard approach to consider the maximum likelihood estimation procedure for the estimation of parameters in statistical modelling. The sample likelihood function has a closed form representation only if the two densities in the integrand are conjugate to each other. In case of any non- conjugate pair, no closed form representation exists. In such situations, we need to approximate the integral by making use of some numerical techniques. A first or second order Laplace approximation or the (adaptive) Gauss-Hermite quadrature method can be applied in order to get an approximative objective function. The resulting approximation of the likelihood function still needs to be numerically maximized with respect to all unknown parameters. For such a numerical maximization, all required derivatives are provided in the scope of this work. We explore the use of the (adaptive) Gauss-Hermite quadrature for Generalized Linear Mixed Models, when the conditional density of the response given the random effects is a member of the linear exponential family and the random effects are Gaussian.
2010. 120 S.
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Basheer Ahmad:Direct Likelihood Approximations for Generalized Linear Mixed Models : An Adaptive Approach
- Livres de poche 2010, ISBN: 3639286936
[EAN: 9783639286939], Neubuch, [PU: VDM Verlag Dr. Müller], nach der Bestellung gedruckt Neuware -It is a standard approach to consider the maximum likelihood estimation procedure for the… Plus…
[EAN: 9783639286939], Neubuch, [PU: VDM Verlag Dr. Müller], nach der Bestellung gedruckt Neuware -It is a standard approach to consider the maximum likelihood estimation procedure for the estimation of parameters in statistical modelling. The sample likelihood function has a closed form representation only if the two densities in the integrand are conjugate to each other. In case of any non- conjugate pair, no closed form representation exists. In such situations, we need to approximate the integral by making use of some numerical techniques. A first or second order Laplace approximation or the (adaptive) Gauss-Hermite quadrature method can be applied in order to get an approximative objective function. The resulting approximation of the likelihood function still needs to be numerically maximized with respect to all unknown parameters. For such a numerical maximization, all required derivatives are provided in the scope of this work. We explore the use of the (adaptive) Gauss-Hermite quadrature for Generalized Linear Mixed Models, when the conditional density of the response given the random effects is a member of the linear exponential family and the random effects are Gaussian. 120 pp. Englisch, Books<
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Direct Likelihood Approximations for Generalized Linear Mixed Models
- nouveau livreISBN: 9783639286939
It is a standard approach to consider the maximum likelihood estimation procedure for the estimation of parameters in statistical modelling. The sample likelihood function has a closed fo… Plus…
It is a standard approach to consider the maximum likelihood estimation procedure for the estimation of parameters in statistical modelling. The sample likelihood function has a closed form representation only if the two densities in the integrand are conjugate to each other. In case of any non- conjugate pair, no closed form representation exists. In such situations, we need to approximate the integral by making use of some numerical techniques. A first or second order Laplace approximation or the (adaptive) Gauss-Hermite quadrature method can be applied in order to get an approximative objective function. The resulting approximation of the likelihood function still needs to be numerically maximized with respect to all unknown parameters. For such a numerical maximization, all required derivatives are provided in the scope of this work. We explore the use of the (adaptive) Gauss-Hermite quadrature for Generalized Linear Mixed Models, when the conditional density of the response given the random effects is a member of the linear exponential family and the random effects are Gaussian. Bücher, Hörbücher & Kalender / Bücher / Sachbuch / Naturwissenschaften / Mathematik / Stochastik & Statistik, [PU: VDM Verlag Dr. Müller, Saarbrücken]<
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Basheer Ahmad:Direct Likelihood Approximations for Generalized Linear Mixed Models
- Livres de poche ISBN: 9783639286939
Paperback, [PU: VDM Verlag], It is a standard approach to consider the maximum likelihood estimation procedure for the estimation of parameters in statistical modelling. The sample likeli… Plus…
Paperback, [PU: VDM Verlag], It is a standard approach to consider the maximum likelihood estimation procedure for the estimation of parameters in statistical modelling. The sample likelihood function has a closed form representation only if the two densities in the integrand are conjugate to each other. In case of any non- conjugate pair, no closed form representation exists. In such situations, we need to approximate the integral by making use of some numerical techniques. A first or second order Laplace approximation or the (adaptive) Gauss-Hermite quadrature method can be applied in order to get an approximative objective function. The resulting approximation of the likelihood function still needs to be numerically maximized with respect to all unknown parameters. For such a numerical maximization, all required derivatives are provided in the scope of this work. We explore the use of the (adaptive) Gauss-Hermite quadrature for Generalized Linear Mixed Models, when the conditional density of the response given the random effects is a member of the linear exponential family and the random effects are Gaussian., Probability & Statistics<
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Ahmad, B:Direct Likelihood Approximations for Generalized L
- Livres de poche 2010, ISBN: 9783639286939
Erscheinungsdatum: 09/2010, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Direct Likelihood Approximations for Generalized Linear Mixed Models, Titelzusatz: An Adaptive Ap… Plus…
Erscheinungsdatum: 09/2010, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Direct Likelihood Approximations for Generalized Linear Mixed Models, Titelzusatz: An Adaptive Approach, Autor: Ahmad, Basheer, Verlag: VDM Verlag, Sprache: Englisch, Rubrik: Mathematik // Wahrscheinlichkeitstheorie, Seiten: 120, Informationen: Paperback, Gewicht: 195 gr, Verkäufer: averdo Belletristik, [PU: VDM Verlag Dr. Müller, Saarbrücken]<
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