Asymptotic Normality of Posterior Distributionsin High Dimensional Linear

@inproceedings{ModelsSUBHASHIS1996AsymptoticNO,
  title={Asymptotic Normality of Posterior Distributionsin High Dimensional Linear},
  author={ModelsSUBHASHIS},
  year={1996}
}
  • ModelsSUBHASHIS
  • Published 1996
We study consistency and asymptotic normality of posterior distributions of the regression coeecient in a linear model when the dimension of the parameter grows with the sample size. Under certain growth restrictions on the dimension (depending on the design matrix), we show that the posterior distributions concentrate in neighbourhoods of the true parameter and can be approximated by an appropriate normal distribution. 

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