Results 61 to 70 of about 1,566,040 (193)
Component selection and smoothing in multivariate nonparametric regression
We propose a new method for model selection and model fitting in multivariate nonparametric regression models, in the framework of smoothing spline ANOVA.
Lin, Yi, Zhang, Hao Helen
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Multivariate response directional regression: a projective resampling approach
In high dimensional data analysis, directional regression is a widely used method for implementing linear sufficient dimension reduction by extracting core information from the complex data structure.
Ahreum Lee, Kyongwon Kim
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BAYESIAN MULTIVARIATE POISSON REGRESSION
The paper proposes a regression model for the multivariate Poisson distribution. So far inference in multivariate Poisson distributions has been prevented by the fact that computation of the probability mass function is difficult. Bayesian methods of inference are proposed which are organized around computational methods based on Gibbs sampling with ...
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In this paper, we consider the nonparametric regression problem with multivariate predictors. We provide a characterization of the degrees of freedom and divergence for estimators of the unknown regression function, which are obtained as outputs of ...
Chen, Xi, Lin, Qihang, Sen, Bodhisattva
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Assessing Lodging Severity over an Experimental Maize (Zea mays L.) Field Using UAS Images
Lodging has been recognized as one of the major destructive factors for crop quality and yield, resulting in an increasing need to develop cost-efficient and accurate methods for detecting crop lodging in a routine manner.
Tianxing Chu +4 more
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Forecasting Ozone Density in Tehran Air Using a Smart Data-Driven Approach
Introduction: As a metropolitan area in Iran, Tehran is exposed to damage from air pollution due to its large population and pollutants from various sources. Accordingly, research on damage induced by air pollution in this city seems necessary.
Seyedeh Reyhaneh Shams +4 more
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Uncertainty under a multivariate nested-error regression model with logarithmic transformation [PDF]
Assuming a multivariate linear regression model with one random factor, we consider the parameters defined as exponentials of mixed effects, i.e., linear combinations of fixed and random effects.
Molina, Isabel
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Nan Peng,1 Qinghong He,2 Jie Bai,1 Chen Chen,3 Gordon G Liu1,4 1School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, Jiangsu, 211198, People’s Republic of China; 2Institute of Economics, Chinese Academy of Social ...
Peng N, He Q, Bai J, Chen C, Liu GG
doaj
Multivariate Adaptive Regression Splines
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A pseudo-RIP for multivariate regression
We give a suitable RI-Property under which recent results for trace regression translate into strong risk bounds for multivariate regression.
Giraud, Christophe
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