Results 201 to 210 of about 1,681,604 (218)

Bayesian Adaptive Lasso for the Generalized Poisson Hurdle Model

Journal of Statistical Computation and Simulation
Variable selection is important in statistical inference. In health economics and management, count outcomes are frequently encountered and often have a large proportion of zeros, and these data change the relation between mean and variance in the Poisson distribution setting.
Guoxin Zuo
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Bayesian Adaptive Lasso for Ordinal Regression With Latent Variables

Sociological Methods & Research, 2015
We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model.
Xiang-Nan Feng, Hao-Tian Wu, Xin-Yuan Song   +2 more
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Sparse Bayesian Broad Learning System via Adaptive Lasso Priors for Robust Regression

IEEE Transactions on Neural Networks and Learning Systems
Broad learning system (BLS), as an innovative type of neural network, has demonstrated exceptional performance in regression tasks. Nonetheless, the majority of BLS methods, which rely on the least squares criterion, are highly sensitive to outliers and noisy data, resulting in reduced prediction accuracy. To improve the robustness of broad networks, a
Philip N L Chen, Lijie Wang
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Bayesian Adaptive Lasso Estimation for Partially Linear Hierarchical Spatial Autoregressive Model

Spatial Statistics
Zhimeng Sun
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Bayesian adaptive lasso quantile regression with non-ignorable missing responses

Computational Statistics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ranran Chen, Mai Dao, Keying Ye, Min Wang 0004   +3 more
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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
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Adaptive lasso echo state network based on modified Bayesian information criterion for nonlinear system modeling

Neural Computing and Applications, 2018
Echo state network (ESN), a novel recurrent neural network, has a randomly and sparsely connected reservoir. Since the reservoir size is very large, the collinearity problem may exist in the ESN. To address this problem and get a sparse architecture, an adaptive lasso echo state network (ALESN) is proposed, in which the adaptive lasso algorithm is used
Junfei Qiao 0001, Lei Wang 0173, Cuili Yang   +2 more
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An Adaptive Bayesian Lasso Approach With Spike-and-Slab Priors to Identify Multiple Linear and Nonlinear Effects in Structural Equation Models

Structural Equation Modeling, 2018
In applied research, such as with motivation theories, typically many variables are theoretically implied predictors of an outcome and several interactions are assumed (e.g., Watt, 2004). However, estimation problems that might arise when several interaction and/or quadratic effects are analyzed simultaneously have not been investigated because ...
Holger Brandt, Augustin Kelava, Jenna Cambria   +2 more
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Bayesian Adaptive Lasso for the Detection of Differential Item Functioning in Graded Response Models

Journal of Educational and Behavioral Statistics
The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response models
Na Shan, Ping-Feng Xu
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Bayesian Adaptive Lasso for Detecting Item–Trait Relationship and Differential Item Functioning in Multidimensional Item Response Theory Models

Psychometrika
In multidimensional tests, the identification of latent traits measured by each item is crucial. In addition to item–trait relationship, differential item functioning (DIF) is routinely evaluated to ensure valid comparison among different groups. The two problems are investigated separately in the literature.
Na Shan, Ping-Feng Xu
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