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SEGMENTED REGRESSION WITH ERRORS IN PREDICTORS: SEMI-PARAMETRIC AND PARAMETRIC METHODS
Statistics in Medicine, 1997We consider the estimation of parameters in a particular segmented generalized linear model with additive measurement error in predictors, with a focus on linear and logistic regression. In epidemiologic studies segmented regression models often occur as threshold models, where it is assumed that the exposure has no influence on the response up to a ...
H, Küchenhoff, R J, Carroll
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Semi-parametric nonlinear regression and transformation using functional networks
Computational Statistics & Data Analysis, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Enrique F. Castillo +3 more
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Double Penalized Semi-Parametric Signed-Rank Regression with Adaptive LASSO
Journal of Systems Science and Complexity, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Interpretable semi-parametric regression models with defined error bounds
Neurocomputing, 2014Unreliable extrapolation of data-driven models hinders their applicability not only in safety-related domains. The paper discusses how model interpretability and uncertainty estimates can address this problem. A new semi-parametric approach is proposed for providing an interpretable model with improved accuracy by combining a symbolic regression model ...
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Two Stage Semi Parametric Quantile Regression [PDF]
, 2009 We propose a root n consistent estimator for B0 when the qth conditional quantile of Y given X=x and Z=z takes the semi linear form g(x)+z'B0 where g(.) is an un- known real valued function,B0 a finite dimensional parameter and (X,Z) a couple of explanatory variables.
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Intrinsic semi-parametric regression model on Grassmannian manifolds with applications
Communications in Statistics - Simulation and Computation, 2022Xuanxuan Sheng, Di Xiong, Shihui Ying
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Semi-parametric Bayesian Additive Regression Trees.
CoRR, 2021Estevão B. Prado +4 more
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Semi-Parametric Distributional Regression in Forestry and Ecology
Die neueren Entwicklungen im Bereich der Machine-Learning-Software, etwa das automatische Differenzieren und die JIT-Kompilierung (JIT = Just in Time), haben die Forschung im maschinellen Lernen erheblich verändert. Sie haben die Modellentwicklung beschleunigt und zum Entstehen von KI-Werkzeugen wie dem Chatbot ChatGPT und dem Bildgenerator DALL-E ...Riebl, Hannes +5 more
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