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- W4383613908 abstract "Abbas [1] proposed new hierarchical representation of the adaptive Bayesian lasso model as uniform density , mixing with standard exponential distribution based on a transformation of the mixture of uniform density and a particular gamma distribution formulation provided by Mallick & Yi [2] They consider the new proposed hierarchical formulation model and prior distributions, as well as the full Conditional posterior distributions structural under non conditioning on σ2 which makes the uncertainty, of a unimodal full posterior, Conditioning on σ2 is important, because it guarantees a unimodal full posterior Park and Casella [3]. So, we can conclude that [1] proposed new hierarchical representation utilizing a Non- scale mixture distributions, which needs to deal with this problem . To address this problem we consider new hierarchical representation of the adaptive Bayesian lasso for Tobit model based on scale mixture of Uniform density, mixing with standard exponential distribution." @default.
- W4383613908 created "2023-07-09" @default.
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- W4383613908 date "2021-10-01" @default.
- W4383613908 modified "2023-10-18" @default.
- W4383613908 title "New Scale Mixture for Bayesian Adaptive Lasso Tobit Regression" @default.
- W4383613908 doi "https://doi.org/10.55562/jrucs.v46i1.100" @default.
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