Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Semiparametric Bayesian Estimation under Structural Measurement Error Model

  • Hwang, Jin-Seub (Department of Statistics, Kyungpook National University) ;
  • Kim, Dal-Ho (Department of Statistics, Kyungpook National University)
  • Received : 20100600
  • Accepted : 20100700
  • Published : 2010.07.31
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Abstract

This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

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References

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Cited by

  1. Bayesian Curve-Fitting in Semiparametric Small Area Models with Measurement Errors vol.22, pp.4, 2015, https://doi.org/10.5351/CSAM.2015.22.4.349