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Advances in Ranking and Selection, Multiple Comparisons, and Reliability : Methodology and Applications /

Contributor(s): Balakrishnan, N [editor.] | Nagaraja, H. N [editor.] | Kannan, N [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Statistics for Industry and Technology: Publisher: Boston, MA : Birkhäuser Boston, 2005.Description: XLIV, 412 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9780817644222.Subject(s): Mathematics | Probabilities | Statistics | Mathematics | Probability Theory and Stochastic Processes | Statistical Theory and Methods | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences | Statistics for Life Sciences, Medicine, Health Sciences | Statistics for Business/Economics/Mathematical Finance/InsuranceDDC classification: 519.2 Online resources: Click here to access online
Contents:
Inference -- Score Test: Historical Review and Recent Developments -- EM Algorithm and Optimal Censoring Schemes for Progressively Type-II Censored Bivariate Normal Data -- Inference Guided Data Exploration -- Discriminating Between Normal and Laplace Distributions -- A Simple Classification Rule for Directional Data -- Ranking and Selection -- On Some Ranking and Selection Procedures for MANOVA Models with Applications -- A Restricted Subset Selection Rule for Selecting At Least One of the t Best Normal Populations in Terms of Their Means: Common Known Variance Case -- Selecting the Best Population with Two Controls: An Empirical Bayes Approach -- Simultaneous Selection of Extreme Populations: Optimal Two-stage Decision Rules -- Multiple Comparisons and Tests -- Comparing Variances of Several Measurement Methods Using a Randomized Block Design with Repeat Measurements: A Case Study -- Impact of Missing Data and Imputation Methods on Multiple Test Procedures -- Asymptotic Second-order Efficiency for Two-stage Multiple Comparisons with Components of a Linear Function of Mean Vectors -- Agreement Assessment -- Measuring Agreement in Method Comparison Studies — A Review -- Measures of Concordance for Assessing Agreement in Ratings and Rank Order Data -- Reliability -- Cost-effective Analysis of Optimal Order-replacement Policies -- Estimating Reliabilities Following Purely Sequential Sampling from Exponential Populations -- Empirical Bayes Estimation of Mean Lifetime for an Exponential Distribution: Unequal Sample Sizes Case -- Blostatistics -- Bayesian Analysis of Mixtures of Improper Survival Distributions -- Multivariate Survival Analysis with PVF Frailty Models -- A Two-stage Design for Choosing Among Experimental Treatments in Clinical Trials.
In: Springer eBooksSummary: S. Panchapakesan has made significant contributions to ranking and selection and has published in many other areas of statistics, including order statistics, reliability theory, stochastic inequalities, and inference. Written in his honor, the twenty invited articles in this volume reflect recent advances in these fields and form a tribute to Panchapakesan’s influence and impact on these areas. Thematically organized, the chapters cover a broad range of topics from: * Inference * Ranking and Selection * Multiple Comparisons and Tests * Agreement Assessment * Reliability * Biostatistics Featuring theory, methods, applications, and extensive bibliographies with special emphasis on recent literature, this comprehensive reference work will serve researchers, practitioners, and graduate students in the statistical and applied mathematics communities.
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Inference -- Score Test: Historical Review and Recent Developments -- EM Algorithm and Optimal Censoring Schemes for Progressively Type-II Censored Bivariate Normal Data -- Inference Guided Data Exploration -- Discriminating Between Normal and Laplace Distributions -- A Simple Classification Rule for Directional Data -- Ranking and Selection -- On Some Ranking and Selection Procedures for MANOVA Models with Applications -- A Restricted Subset Selection Rule for Selecting At Least One of the t Best Normal Populations in Terms of Their Means: Common Known Variance Case -- Selecting the Best Population with Two Controls: An Empirical Bayes Approach -- Simultaneous Selection of Extreme Populations: Optimal Two-stage Decision Rules -- Multiple Comparisons and Tests -- Comparing Variances of Several Measurement Methods Using a Randomized Block Design with Repeat Measurements: A Case Study -- Impact of Missing Data and Imputation Methods on Multiple Test Procedures -- Asymptotic Second-order Efficiency for Two-stage Multiple Comparisons with Components of a Linear Function of Mean Vectors -- Agreement Assessment -- Measuring Agreement in Method Comparison Studies — A Review -- Measures of Concordance for Assessing Agreement in Ratings and Rank Order Data -- Reliability -- Cost-effective Analysis of Optimal Order-replacement Policies -- Estimating Reliabilities Following Purely Sequential Sampling from Exponential Populations -- Empirical Bayes Estimation of Mean Lifetime for an Exponential Distribution: Unequal Sample Sizes Case -- Blostatistics -- Bayesian Analysis of Mixtures of Improper Survival Distributions -- Multivariate Survival Analysis with PVF Frailty Models -- A Two-stage Design for Choosing Among Experimental Treatments in Clinical Trials.

S. Panchapakesan has made significant contributions to ranking and selection and has published in many other areas of statistics, including order statistics, reliability theory, stochastic inequalities, and inference. Written in his honor, the twenty invited articles in this volume reflect recent advances in these fields and form a tribute to Panchapakesan’s influence and impact on these areas. Thematically organized, the chapters cover a broad range of topics from: * Inference * Ranking and Selection * Multiple Comparisons and Tests * Agreement Assessment * Reliability * Biostatistics Featuring theory, methods, applications, and extensive bibliographies with special emphasis on recent literature, this comprehensive reference work will serve researchers, practitioners, and graduate students in the statistical and applied mathematics communities.

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