Results 141 to 150 of about 2,889,354 (160)

Bayesian reciprocal LASSO quantile regression

Communications in Statistics - Simulation and Computation, 2020
The reciprocal LASSO estimate for linear regression corresponds to a posterior mode when independent inverse Laplace priors are assigned on the regression coefficients.
Rahim Alhamzawi, Himel Mallick
openaire   +2 more sources

Gene Selection for Microarray Gene Expression Classification Using Bayesian Lasso Quantile Regression

Computers in Biology and Medicine, 2018
Gene selection has been proven to be an effective way to improve the results of many classification methods. However, existing gene selection techniques in binary classification regression are sensitive to outliers of the data, heteroskedasticity or other anomalies of the latent response.
Haithem Taha Mohammad Ali, Zakariya Yahya Algamal, Rahim Alhamzawi   +2 more
exaly   +4 more sources

Bayesian Adaptive Lasso for Quantile Regression Models With Nonignorably Missing Response Data

Communications in Statistics Part B: Simulation and Computation, 2019
Handling data with the nonignorably missing mechanism is still a challenging problem in statistics.
Niansheng Tang
exaly   +3 more sources

Bayesian LASSO-Regularized quantile regression for linear regression models with autoregressive errors

Communications in Statistics - Simulation and Computation, 2017
Quantile regression (QR) is a natural alternative for depicting the impact of covariates on the conditional distributions of a outcome variable instead of the mean.
Yuzhu Tian, Silian Shen, Ge Lu, Man-Lai Tang, Maozai Tian   +4 more
openaire   +2 more sources

Bayesian Adaptive Lasso Quantile Regression With Non-Ignorable Missing Responses

Computational Statistics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Keying Ye
exaly   +5 more sources

Bayesian Binary Quantile Regression Adaptive Lasso for Modelling Hypertension: A Bootstrap Based Consistency Analysis

Communications in Statistics Case Studies Data Analysis and Applications
Ferra Yanuar, Dodi Devianto
exaly   +2 more sources

Modeling Classification of Stunting Toddler Height Using Bayesian Binary Quantile Regression With Penalized Lasso

Mathline Jurnal Matematika Dan Pendidikan Matematika
Stunting is a child who has a height that is shorter than the age standard. One of the main indicators of stunting is a height that is lower than the standard for toddlers. Stunting in Indonesia is of great concern due to the high prevalence of stunting.
Maiyastri Maiyastri
exaly   +2 more sources

Regularized Bayesian Quantile Regression [PDF]

Communications in Statistics Part B: Simulation and Computation, 2018
A number of nonstationary models have been developed to estimate extreme events as function of covariates. A quantile regression (QR) model is a statistical approach intended to estimate and conduct inference about the conditional quantile functions.
André St-Hilaire, Salah-Eddine El Adlouni   +1 more
exaly   +2 more sources

Variables selection which effecting on enlarged prostate gland by Bayesian Lasso quantile regression

AIP Conference Proceedings, 2023
Amira Safer Mathkhor, Fadel Hamid Hadi, Ashraf M. Shareef   +2 more
openaire   +1 more source

Bayesian Reciprocal LASSO Quantile Regression

Communications in Statistics Part B: Simulation and Computation, 2022
Rahim Alhamzawi, Himel Mallick
exaly