Results 11 to 20 of about 5,885 (195)
Semiparametric Regression Pursuit. [PDF]
Stat Sin, 2012 The semiparametric partially linear model allows flexible modeling of covariate effects on the response variable in regression. It combines the flexibility of nonparametric regression and parsimony of linear regression. The most important assumption in the existing methods for the estimation in this model is to assume a priori that it is known which ...
Huang J, Wei F, Ma S.
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Endogeneity in Semiparametric Threshold Regression [PDF]
SSRN Electronic Journal, 2017 This paper estimates threshold regression models with an endogenous threshold variable using a nonparametric control function approach. Assuming diminishing threshold effects, we derive the consistency and limiting distribution of our proposed estimator constructed from the series approximation method for weakly dependent data.
Kourtellos, Andros +2 more
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Semiparametric Tail Index Regression [PDF]
Journal of Business & Economic Statistics, 2020 Abstract–Understanding why extreme events occur is often of major scientific interest in many fields. The occurrence of these events naturally depends on explanatory variables, but there is a severe lack of flexible models with asymptotic theory for understanding this dependence, especially when variables can affect the outcome nonlinearly.
Rui Li, Chenlei Leng, Jinhong You
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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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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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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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