Reducing Bias and Mean Squared Error Associated With Regression-Based Odds Ratio Estimators. [PDF]
Lyles RH, Guo Y, Greenland S.
europepmc +1 more source
Smoothness of in vivo spectral baseline determined by mean-square error. [PDF]
Zhang Y, Shen J.
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Bagging-based heteroscedasticity-adjusted ridge estimators in the linear regression model
The existence of multicollinearity between independent variables and heteroscedastic error has a colossal impact on the performance of the ordinary least square (OLS) estimator and its covariance matrix.
doaj +1 more source
This paper provides an in-depth analysis and performance evaluation of four Solar Radiance (SR) prediction models. The prediction is ensured for a period ranging from a few hours to several days of the year.
Boumediene Ladjal +7 more
doaj +1 more source
Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression. [PDF]
Stolte M +6 more
europepmc +1 more source
Leveraging generative neural networks for accurate, diverse, and robust nanoparticle design. [PDF]
Rahman T +9 more
europepmc +1 more source
Denoising autoencoder framework for reconstructing missing periodontal clinical records. [PDF]
Mathew A, Yadalam PK.
europepmc +1 more source
Redefining multi-target weather forecasting with a novel deep learning model: Hierarchical temporal convolutional long short-term memory with attention (HTC-LSTM-Attn) in Bangladesh. [PDF]
Kabir MA, Chakma C.
europepmc +1 more source
Modelling C-arm fluoroscopy and operating table kinematics via machine learning. [PDF]
Jaheen F, Gutta V, Fallavollita P.
europepmc +1 more source

