Bayesian composite quantile regression. Journal of Statistical Computation and Simulation Vol 85, Issue 18.Huang, H., & Chen, Z. "Bayesian composite quantile regression. ".Journal of Statistical Computation and
The model expands the flexibility of linear regression to account for heterogeneity among data and allows us to establish the equivalence between maximum likelihood estimation of the model parameters and the composite quantile regression (CQR) estimation developed by......
(2016) examined Bayesian composite quantile regression with adaptive group Lasso penalties. In the era of big data, Bayesian methods have been extensively applied across various statistical frameworks. Xu and Zhang (2013) explored Bayesian inference for semiparametric joint mean and variance models using...
The composite SDM or SDEM can be created by adjusting the parent class of ‘SpatialAR’ or ‘SpatialEM’ to ‘SpatialLX’. At the moment, layered adjustment to filtered quantities, as used for the SAC model, is not supported. To simplify the link between this object-oriented core to the...
Bayesian optimization (BO) is a powerful approach for seeking the global optimum of expensive black-box functions and has proven successful for fine tuning
et al. Creation of regression analysis for estimation of carbon fiber reinforced polymer-steel bond strength. Steel and Composite Structures, 2024, 51(5): 509-527. DOI:10.12989/scs.2024.51.5.509 118. Tiwari, S., Das, S.K., Mohanty, M. et al. Improved prediction of soil liquefaction ...
The proposed algorithms have been applied to two different experiments, as per Sections 4.1 Data-driven example: Fatigue in composite materials, 4.2 Engineering case study: Accelerations in seismic events. Their performance have been evaluated and compared against the state-of-the-art RNN. The detail...
we study the Bayesian composite quantile regression with adaptive group Lasso penalty.The distinguishing characteristic of the newly proposed method is completely data adaptive without requiring prior knowledge of the error distribution.Extensive simulations and two real data examples are used to examine ...
The ADI is a composite measure of seventeen indicators ranging from 1 (less deprived) to 100 (most deprived) constructed from weighted factor score coefficients to describe a neighborhood’s relative socioeconomic position across three domains: financial strength, economic hardship and inequality, and ...
Predicting thrust force during drilling of composite laminates with step drills through the Gaussian process regression Multidiscip. Model. Mater. Struct., 18 (5) (2022), pp. 845-855, 10.1108/MMMS-07-2022-0123 View in ScopusGoogle Scholar [168] Zhang Y., Xu X. Gaussian process modeling of...