Results 11 to 20 of about 5,704 (194)
Robust Variable Selection for Single-Index Varying-Coefficient Model with Missing Data in Covariates
Mathematics, 2022 As applied sciences grow by leaps and bounds, semiparametric regression analyses have broad applications in various fields, such as engineering, finance, medicine, and public health.
Yunquan Song, Yaqi Liu, Hang Su
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On Semiparametric Mode Regression Estimation [PDF]
Communications in Statistics - Theory and Methods, 2010 It has been found that, for a variety of probability distributions, there is a surprising linear relation between mode, mean, and median. In this article, the relation between mode, mean, and median regression functions is assumed to follow a simple parametric model.
Gannoun, Ali, Saracco, Jerôme, Yu, Y.
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Semiparametric Regression Analysis via Infer.NET
Journal of Statistical Software, 2018 We provide several examples of Bayesian semiparametric regression analysis via the Infer.NET package for approximate deterministic inference in Bayesian models.
Jan Luts +3 more
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Real-Time Semiparametric Regression [PDF]
Journal of Computational and Graphical Statistics, 2014 We develop algorithms for performing semiparametric regression analysis in real time, with data processed as it is collected and made immediately available via modern telecommunications technologies. Our definition of semiparametric regression is quite broad and includes, as special cases, generalized linear mixed models, generalized additive models ...
Luts, Jan +2 more
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Mathematics, 2023 Multivariate “Bayesian” regression via a shared component model has gained popularity in recent years, particularly in modeling and mapping the risks associated with multiple diseases.
I. Gede Nyoman Mindra Jaya +5 more
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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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A More Accurate Estimation of Semiparametric Logistic Regression
Mathematics, 2021 Growing interest in genomics research has called for new semiparametric models based on kernel machine regression for modeling health outcomes. Models containing redundant predictors often show unsatisfactory prediction performance.
Xia Zheng +3 more
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SEMIPARAMETRIC PENALIZED SPLINE REGRESSION [PDF]
Bulletin of informatics and cybernetics, 2012 In this paper, we propose a new semiparametric regression estimator by using a hybrid technique of a parametric approach and a nonparametric penalized spline method. The overall shape of the true regression function is captured by the parametric part, while its residual is consistently estimated by the nonparametric part.
Yoshida, Takuma, Naito, Kanta
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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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Media Statistika, 2020 Confidence interval estimation is important in statistical inference for the parameters of the regression model, but the theory of confidence interval estimation for multi-response semiparametric regression model parameters based on the truncated spline ...
Lilik Hidayati +2 more
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