Results 11 to 20 of about 15,261 (244)
Efficient estimation in semiparametric GARCH models [PDF]
Journal of Econometrics, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Drost, F.C., Klaassen, C.A.J.
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Energies, 2020 We propose the use of wavelet-based semiparametric models for forecasting the value-at-risk (VaR) and expected shortfall (ES) in the crude oil market. We compared the forecast outcomes across different time scales for three semiparametric models, three ...
Lu Yang, Shigeyuki Hamori
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SEMIPARAMETRIC MULTIVARIATE VOLATILITY MODELS [PDF]
Econometric Theory, 2007 Summary: We consider a model for a multivariate time series where the conditional covariance matrix is a function of a finite-dimensional parameter and the innovation distribution is nonparametric. The semiparametric lower bound for the estimation of the Euclidean parameter is characterized, and it is shown that adaptive estimation without ...
Hafner, C.M., Rombouts, J.V.K.
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Apstract: Applied Studies in Agribusiness and Commerce, 2017 This paper introduces the semiparametric error correction model for estimation of export-import relationship as an alternative to the least squares approach.
Henry De-Graft Acquah +1 more
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bsamGP: An R Package for Bayesian Spectral Analysis Models Using Gaussian Process Priors
Journal of Statistical Software, 2019 The Bayesian spectral analysis model (BSAM) is a powerful tool to deal with semiparametric methods in regression and density estimation based on the spectral representation of Gaussian process priors. The bsamGP package for R provides a comprehensive set
Seongil Jo +3 more
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Generalizing sample tree information with semiparametric and parametric models.
Silva Fennica, 1995 Semiparametric models, ordinary regression models and mixed models were compared for modelling stem volume in National Forest Inventory data. MSE was lowest for the mixed model.
Kangas, Annika, Korhonen, Kari
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A semiparametric cluster detection method — a comprehensive power comparison with Kulldorff's method
International Journal of Health Geographics, 2009 Background A semiparametric density ratio method which borrows strength from two or more samples can be applied to moving window of variable size in cluster detection. The method requires neither the prior knowledge of the underlying distribution nor the
Kedem Benjamin, Wen Shihua
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E-Jurnal Matematika, 2017 Semiparametric regression is a regression model that includes parametric components and nonparametric components in a model. The regression model in this research is truncated spline semiparametric regression with case studies of patients with Dengue ...
NI WAYAN MERRY NIRMALA YANI +2 more
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Investigation of Parametric, Non-Parametric and Semiparametric Methods in Regression Analysis
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2022 Regression analysis is known as statistical methods applied to model and analyze the relationship between variables. Regression method can be examined as parametric, non-parametric and semiparametric regression methods.The parametric regression method ...
Esra Yavuz, Mustafa Şahin
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Semiparametric modelling of multicategorical data [PDF]
Journal of Statistical Computation and Simulation, 2004 Parametric multicategorical models are an established tool in statistical data analysis. Alternative semi-parametric models are introduced where part of the explanatory variables is still linearly parametrized and the rest is given as a sum of unspecified functions of the explanatory variables.
Tutz, Gerhard, Scholz, T.
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