Results 31 to 40 of about 5,788,827 (317)
Linear regression model using bayesian approach for energy performance of residential building
International Conference on Computer Science and Computational Intelligence, 2018 In the statistics there are two types of points of view, Frequentist and Bayesian. The difference between Frequentist and Bayesian is the point of view in terms of looking at a parameter.
S. D. Permai, H. Tanty
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Choosing the Right Spatial Weighting Matrix in a Quantile Regression Model [PDF]
, 2013 This paper proposes computationally tractable methods for selecting the appropriate spatial weighting matrix in the context of a spatial quantile regression model.
Kostov, Phillip
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Environmental Research, 2016 Existing evidence suggests that ambient ultrafine particles (UFPs) (
S. Weichenthal +5 more
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RESEARCH ON GPS HEIGHT FITTING BASED ON LINEAR REGRESSION MODEL [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 This paper mainly expounds the parameter estimation method, the outlier diagnosis and the establishment of the optimal regression equation in the linear regression model theory, the analysis of the principle of the polynomial fitting model, the ...
K. Y. Yang +7 more
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On the First Order Regression Procedure of Estimation for Incomplete Regression Models [PDF]
, 1999 This article discusses some properties of the first order regression method for imputation of missing values on an explanatory variable in linear regression model and presents an estimation strategy based on hypothesis ...
Srivastava, V. K., Toutenburg, Helge
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Stein-Rule Estimation under an Extended Balanced Loss Function [PDF]
, 2007 This paper extends the balanced loss function to a more general set up. The ordinary least squares and Stein-rule estimators are exposed to this general loss function with quadratic loss structure in a linear regression model.
---, Shalabh +2 more
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Generating atmospheric forcing perturbations for an ocean data assimilation ensemble
Tellus: Series A, Dynamic Meteorology and Oceanography, 2019 Running ensemble of reanalyses or forecasts has proved successful at improving their performances, despite the cost. Generating ensemble simulations requires generating perturbations within the models, and for the assimilated observations and subsidiary ...
Isabelle Mirouze, Andrea Storto
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Hidden Markov Linear Regression Model and its Parameter Estimation
IEEE Access, 2020 This article first defines a hidden Markov linear regression model for the purpose of further studying the mutual transformation between different states in the linear regression model, and the regression relationship between the dependent variable and ...
Hefei Liu, Kunqjnu Wang, Yong Li
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, 2015 Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes.
Frank, Eibe +2 more
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Adiabatic quantum linear regression [PDF]
Scientific Reports, 2020 A major challenge in machine learning is the computational expense of training these models. Model training can be viewed as a form of optimization used to fit a machine learning model to a set of data, which can take up significant amount of time on ...
Prasanna Date, T. Potok
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