Biostatistics 602 Statistical Inference Lecture 26 Final

Biostatistics 602 Statistical Inference Lecture 26 Final-Free PDF

  • Date:28 Jun 2020
  • Views:3
  • Downloads:0
  • Pages:155
  • Size:777.89 KB

Share Pdf : Biostatistics 602 Statistical Inference Lecture 26 Final

Download and Preview : Biostatistics 602 Statistical Inference Lecture 26 Final


Report CopyRight/DMCA Form For : Biostatistics 602 Statistical Inference Lecture 26 Final


Transcription:

Review P1 P2 P3 P4 Wrap up,Review of the second half. Rao Blackwell, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 2 31. Review P1 P2 P3 P4 Wrap up,Review of the second half. Rao Blackwell If W X is an unbiased estimator of,T E W X T is a better unbiased estimator for a. su cient statistic,Uniqueness of MVUE, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 2 31.
Review P1 P2 P3 P4 Wrap up,Review of the second half. Rao Blackwell If W X is an unbiased estimator of,T E W X T is a better unbiased estimator for a. su cient statistic, Uniqueness of MVUE Theorem 7 3 19 Best unbiased estimator is. MVUE and UE of zeros, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 2 31. Review P1 P2 P3 P4 Wrap up,Review of the second half.
Rao Blackwell If W X is an unbiased estimator of,T E W X T is a better unbiased estimator for a. su cient statistic, Uniqueness of MVUE Theorem 7 3 19 Best unbiased estimator is. MVUE and UE of zeros Theorem 7 3 20 Best unbiased estimator is. uncorrelated with any unbiased estimators of zero,UMVE by complete su cient statistics. Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 2 31. Review P1 P2 P3 P4 Wrap up,Review of the second half. Rao Blackwell If W X is an unbiased estimator of,T E W X T is a better unbiased estimator for a.
su cient statistic, Uniqueness of MVUE Theorem 7 3 19 Best unbiased estimator is. MVUE and UE of zeros Theorem 7 3 20 Best unbiased estimator is. uncorrelated with any unbiased estimators of zero, UMVE by complete su cient statistics Theorem 7 3 23 Any function. of complete su cient statistic is the best unbiased estimator. for its expected value, How to get UMVUE Strategies to obtain best unbiased estimators. Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 2 31. Review P1 P2 P3 P4 Wrap up,Review of the second half. Rao Blackwell If W X is an unbiased estimator of,T E W X T is a better unbiased estimator for a.
su cient statistic, Uniqueness of MVUE Theorem 7 3 19 Best unbiased estimator is. MVUE and UE of zeros Theorem 7 3 20 Best unbiased estimator is. uncorrelated with any unbiased estimators of zero, UMVE by complete su cient statistics Theorem 7 3 23 Any function. of complete su cient statistic is the best unbiased estimator. for its expected value, How to get UMVUE Strategies to obtain best unbiased estimators. Condition a simple unbiased estimator on complete,su cient statistics. Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 2 31. Review P1 P2 P3 P4 Wrap up,Review of the second half.
Rao Blackwell If W X is an unbiased estimator of,T E W X T is a better unbiased estimator for a. su cient statistic, Uniqueness of MVUE Theorem 7 3 19 Best unbiased estimator is. MVUE and UE of zeros Theorem 7 3 20 Best unbiased estimator is. uncorrelated with any unbiased estimators of zero, UMVE by complete su cient statistics Theorem 7 3 23 Any function. of complete su cient statistic is the best unbiased estimator. for its expected value, How to get UMVUE Strategies to obtain best unbiased estimators. Condition a simple unbiased estimator on complete,su cient statistics.
Come up with a function of su cient statistic whose. expected value is, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 2 31. Review P1 P2 P3 P4 Wrap up,Bayesian Framework,Prior distribution. Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 3 31. Review P1 P2 P3 P4 Wrap up,Bayesian Framework,Prior distribution. Sampling distribution x fX x, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 3 31. Review P1 P2 P3 P4 Wrap up,Bayesian Framework,Prior distribution.
Sampling distribution x fX x,Joint distribution f x. Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 3 31. Review P1 P2 P3 P4 Wrap up,Bayesian Framework,Prior distribution. Sampling distribution x fX x,Joint distribution f x. Marginal distribution m x f x d, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 3 31. Review P1 P2 P3 P4 Wrap up,Bayesian Framework,Prior distribution.
Sampling distribution x fX x,Joint distribution f x. Marginal distribution m x f x d,Posterior distribution x m x. Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 3 31. Review P1 P2 P3 P4 Wrap up,Bayesian Framework,Prior distribution. Sampling distribution x fX x,Joint distribution f x. Marginal distribution m x f x d,Posterior distribution x m x.
Bayes Estimator is a posterior mean of E x, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 3 31. Review P1 P2 P3 P4 Wrap up,Bayesian Decision Theory. Loss Function L e g 2, Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 4 31. Biostatistics 602 Statistical Inference Lecture 26 Final Exam Review amp Practice Problems for the Final Hyun Min Kang Apil 23rd 2013 Hyun Min Kang Biostatistics 602 Lecture 26 Apil 23rd 2013 1 31

Related Books