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    CSDA
    2007
    104views more  CSDA 2007»
    Archimedean copula estimation using Bayesian splines smoothing techniques
    13 years 5 months ago
    Archimedean copula estimation using Bayesian splines smoothing techniques
    Download  www.stat.ucl.ac.be
    Copulas enable to specify multivariate distributions with given marginals.Various parametric proposals were made in the literature for these quantities, mainly in the bivariate ca...
    Philippe Lambert
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    CSDA
    2007
    123views more  CSDA 2007»
    Bayesian estimation of unrestricted and order-restricted association models for a two-way contingency table
    13 years 5 months ago
    Bayesian estimation of unrestricted and order-restricted association models for a two-way contingency table
    Download  stat-athens.aueb.gr
    In two-way contingency tables analysis, a popular class of models for describing the structure of the association between the two categorical variables are the so-called “associ...
    G. Iliopoulos, Maria Kateri, Ioannis Ntzoufras
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    CSDA
    2007
    98views more  CSDA 2007»
    A new Bayes estimate of the change point in the hazard function
    13 years 5 months ago
    A new Bayes estimate of the change point in the hazard function
    Download  yunus.hacettepe.edu.tr
    An efficient estimate for the change point in the hazard function is obtained. This is based on a Bayesian estimator which uses equations concerning the parameters of a recently ...
    Durdu Sertkaya Karasoy, Cem Kadilar
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    CSDA
    2007
    85views more  CSDA 2007»
    Markov models for digraph panel data: Monte Carlo-based derivative estimation
    13 years 5 months ago
    Markov models for digraph panel data: Monte Carlo-based derivative estimation
    Download  stat.gamma.rug.nl
    A parametric, continuous-time Markov model for digraph panel data is considered. The parameter is estimated by the method of moments. A convenient method for estimating the varian...
    Michael Schweinberger, Tom A. B. Snijders
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    CSDA
    2007
    69views more  CSDA 2007»
    Prediction intervals for regression models
    13 years 5 months ago
    Prediction intervals for regression models
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    David J. Olive
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    CSDA
    2007
    106views more  CSDA 2007»
    Parsimonious additive models
    13 years 5 months ago
    Parsimonious additive models
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    A new method for function estimation and variable selection, specifically designed for additive models fitted by cubic splines is proposed.This new method involves regularizing ...
    Marta Avalos, Yves Grandvalet, Christophe Ambroise
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    CSDA
    2007
    86views more  CSDA 2007»
    A convenient way of generating gamma random variables using generalized exponential distribution
    13 years 5 months ago
    A convenient way of generating gamma random variables using generalized exponential distribution
    Download  home.iitk.ac.in
    In this paper we propose a very convenient way to generate gamma random variables using generalized exponential distribution, when the shape parameter lies between 0
    Debasis Kundu, Rameshwar D. Gupta
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    CSDA
    2007
    202views more  CSDA 2007»
    Bayesian estimation of the Gaussian mixture GARCH model
    13 years 5 months ago
    Bayesian estimation of the Gaussian mixture GARCH model
    Download  docubib.uc3m.es
    In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions. This GARCH model...
    María Concepción Ausín, Pedro...
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    CSDA
    2007
    82views more  CSDA 2007»
    On hybrid methods of inverse regression-based algorithms
    13 years 5 months ago
    On hybrid methods of inverse regression-based algorithms
    Download  www.rbm.hiroshima-u.ac.jp
    Li-Xing Zhu, Megu Ohtaki, Yingxing Li
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    CSDA
    2007
    65views more  CSDA 2007»
    Multivariate mixed normal conditional heteroskedasticity
    13 years 5 months ago
    Multivariate mixed normal conditional heteroskedasticity
    Download  www.core.ucl.ac.be
    L. Bauwens, C. M. Hafner, Jeroen V. K. Rombouts
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