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Bayesian quantile regression with approximate likelihood
Yang Feng,
Yuguo Chen
, Xuming He
Statistics
Information Trust Institute
Coordinated Science Lab
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Dive into the research topics of 'Bayesian quantile regression with approximate likelihood'. Together they form a unique fingerprint.
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Keyphrases
Algorithmic Convergence
33%
Approximate Likelihood
100%
Asymptotic Theory
33%
Bayesian Framework
33%
Bayesian Quantile Regression
100%
Challenging Problems
33%
Convergence Results
33%
Density Method
33%
Explanatory Variables
33%
Frequentist Approach
33%
Full Likelihood
33%
Global Efficiency
33%
Integrated Likelihood
33%
Joint Posterior Distribution
33%
Linear Interpolation
33%
Markov Chain Monte Carlo Algorithm
33%
Multiple Quantiles
33%
Parametric Form
33%
Quantile Regression
66%
Quantile Regression Model
33%
Response Variable
33%
Statistical Approximation
33%
Mathematics
Approximates
100%
Asymptotic Theory
20%
Bayesian
100%
Convergence Result
20%
Explanatory Variable
20%
Frequentist Approach
20%
Joint Posterior Distribution
20%
Linear Interpolation
20%
Markov Chain Monte Carlo
20%
Monte Carlo Algorithm
20%
Parametric Form
20%
Quantile
100%
Quantile Regression
100%
Response Variable
20%
Economics, Econometrics and Finance
Bayesian
100%
Markov Chain Monte Carlo
25%