Schade – dieser Artikel ist leider ausverkauft. Sobald wir wissen, ob und wann der Artikel wieder verfügbar ist, informieren wir Sie an dieser Stelle.
- Format: PDF
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei
bücher.de, um das eBook-Abo tolino select nutzen zu können.
Hier können Sie sich einloggen
Hier können Sie sich einloggen
Sie sind bereits eingeloggt. Klicken Sie auf 2. tolino select Abo, um fortzufahren.
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
Praise for the Second Edition "This book should be an essential part of the personal library of every practicing statistician."--Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given…mehr
- Geräte: PC
- eBook Hilfe
Praise for the Second Edition "This book should be an essential part of the personal library of every practicing statistician."--Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: * The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition * New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics * Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.
Produktdetails
- Produktdetails
- Verlag: John Wiley & Sons
- Seitenzahl: 848
- Erscheinungstermin: 6. November 2013
- Englisch
- ISBN-13: 9781118677995
- Artikelnr.: 39973740
- Verlag: John Wiley & Sons
- Seitenzahl: 848
- Erscheinungstermin: 6. November 2013
- Englisch
- ISBN-13: 9781118677995
- Artikelnr.: 39973740
MYLES HOLLANDER is Robert O. Lawton Distinguished Professor of Statistics and Professor Emeritus at the Florida State University in Tallahassee. He served as editor of the Theory and Methods Section of the Journal of the American Statistical Association, 1993-96, and he received the Gottfried E. Noether Senior Scholar Award from the American Statistical Association in 2003. DOUGLAS A. WOLFE is Professor and Chair Emeritus in the Department of Statistics at Ohio State University in Columbus. He is a two-time recipient of the Ohio State University Alumni Distinguished Teaching Award, in 1973-74 and 1988-89. ERIC CHICKEN is Associate Professor at the Florida State University in Tallahassee. He is active in modern nonparametric statistics research fields, including functional analysis, sequential methods, and complex system applications.
Preface xiii 1. Introduction 1 1.1. Advantages of Nonparametric Methods 1 1.2. The Distribution
Free Property 2 1.3. Some Real
World Applications 3 1.4. Format and Organization 6 1.5. Computing with R 8 1.6. Historical Background 9 2. The Dichotomous Data Problem 11 Introduction 11 2.1. A Binomial Test 11 2.2. An Estimator for the Probability of Success 22 2.3. A Confidence Interval for the Probability of Success (Wilson) 24 2.4. Bayes Estimators for the Probability of Success 33 3. The One
Sample Location Problem 39 Introduction 39 Paired Replicates Analyses by Way of Signed Ranks 39 3.1. A Distribution
Free Signed Rank Test (Wilcoxon) 40 3.2. An Estimator Associated with Wilcoxon's Signed Rank Statistic (Hodges
Lehmann) 56 3.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Signed Rank Test (Tukey) 59 Paired Replicates Analyses by Way of Signs 63 3.4. A Distribution
Free Sign Test (Fisher) 63 3.5. An Estimator Associated with the Sign Statistic (Hodges
Lehmann) 76 3.6. A Distribution
Free Confidence Interval Based on the Sign Test (Thompson, Savur) 80 One
Sample Data 84 3.7. Procedures Based on the Signed Rank Statistic 84 3.8. Procedures Based on the Sign Statistic 90 3.9. An Asymptotically Distribution
Free Test of Symmetry (Randles
Fligner
Policello
Wolfe, Davis
Quade) 94 Bivariate Data 102 3.10. A Distribution
Free Test for Bivariate Symmetry (Hollander) 102 3.11. Efficiencies of Paired Replicates and One
Sample Location Procedures 112 4. The Two
Sample Location Problem 115 Introduction 115 4.1. A Distribution
Free Rank Sum Test (Wilcoxon, Mann and Whitney) 115 4.2. An Estimator Associated with Wilcoxon's Rank Sum Statistic (Hodges
Lehmann) 136 4.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Rank Sum Test (Moses) 142 4.4. A Robust Rank Test for the Behrens
Fisher Problem (Fligner
Policello) 145 4.5. Efficiencies of Two
Sample Location Procedures 149 5. The Two
Sample Dispersion Problem and Other Two
Sample Problems 151 Introduction 151 5.1. A Distribution
Free Rank Test for Dispersion
Medians Equal (Ansari
Bradley) 152 5.2. An Asymptotically Distribution
Free Test for Dispersion Based on the Jackknife
Medians Not Necessarily Equal (Miller) 169 5.3. A Distribution
Free Rank Test for Either Location or Dispersion (Lepage) 181 5.4. A Distribution
Free Test for General Differences in Two Populations (Kolmogorov
Smirnov) 190 5.5. Efficiencies of Two
Sample Dispersion and Broad Alternatives Procedures 200 6. The One
Way Layout 202 Introduction 202 6.1. A Distribution
Free Test for General Alternatives (Kruskal
Wallis) 204 6.2. A Distribution
Free Test for Ordered Alternatives (Jonckheere
Terpstra) 215 6.3. Distribution
Free Tests for Umbrella Alternatives (Mack
Wolfe) 225 6.3A. A Distribution
Free Test for Umbrella Alternatives, Peak Known (Mack
Wolfe) 226 6.3B. A Distribution
Free Test for Umbrella Alternatives, Peak Unknown (Mack
Wolfe) 241 6.4. A Distribution
Free Test for Treatments Versus a Control (Fligner
Wolfe) 249 Rationale For Multiple Comparison Procedures 255 6.5. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
General Configuration (Dwass, Steel, and Critchlow
Fligner) 256 6.6. Distribution
Free One
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
Ordered Treatment Effects (Hayter
Stone) 265 6.7. Distribution
Free One
Sided Treatments
Versus
Control Multiple Comparisons Based on Joint Rankings (Nemenyi, Damico
Wolfe) 271 6.8. Contrast Estimation Based on Hodges
Lehmann Two
Sample Estimators (Spjøtvoll) 278 6.9. Simultaneous Confidence Intervals for All Simple Contrasts (Critchlow
Fligner) 282 6.10. Efficiencies of One
Way Layout Procedures 287 7. The Two
Way Layout 289 Introduction 289 7.1. A Distribution
Free Test for General Alternatives in a Randomized Complete Block Design (Friedman, Kendall
Babington Smith) 292 7.2. A Distribution
Free Test for Ordered Alternatives in a Randomized Complete Block Design (Page) 304 Rationale for Multiple Comparison Procedures 315 7.3. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Friedman Rank Sums
General Configuration (Wilcoxon, Nemenyi, McDonald
Thompson) 316 7.4. Distribution
Free One
Sided Treatments Versus Control Multiple Comparisons Based on Friedman Rank Sums (Nemenyi, Wilcoxon
Wilcox, Miller) 322 7.5. Contrast Estimation Based on One
Sample Median Estimators (Doksum) 328 Incomplete Block Data
Two
Way Layout with Zero or One Observation Per Treatment
Block Combination 331 7.6. A Distribution
Free Test for General Alternatives in a Randomized Balanced Incomplete Block Design (BIBD) (Durbin
Skillings
Mack) 332 7.7. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for Balanced Incomplete Block Designs (Skillings
Mack) 341 7.8. A Distribution
Free Test for General Alternatives for Data From an Arbitrary Incomplete Block Design (Skillings
Mack) 343 Replications
Two
Way Layout with at Least One Observation for Every Treatment
Block Combination 354 7.9. A Distribution
Free Test for General Alternatives in a Randomized Block Design with an Equal Number c(>1) of Replications Per Treatment
Block Combination (Mack
Skillings) 354 7.10. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for a Two
Way Layout with an Equal Number of Replications in Each Treatment
Block Combination (Mack
Skillings) 367 Analyses Associated with Signed Ranks 370 7.11. A Test Based on Wilcoxon Signed Ranks for General Alternatives in a Randomized Complete Block Design (Doksum) 370 7.12. A Test Based on Wilcoxon Signed Ranks for Ordered Alternatives in a Randomized Complete Block Design (Hollander) 376 7.13. Approximate Two
Sided All
Treatments Multiple Comparisons Based on Signed Ranks (Nemenyi) 379 7.14. Approximate One
Sided Treatments
Versus
Control Multiple Comparisons Based on Signed Ranks (Hollander) 382 7.15. Contrast Estimation Based on the One
Sample Hodges
Lehmann Estimators (Lehmann) 386 7.16. Efficiencies of Two
Way Layout Procedures 390 8. The Independence Problem 393 Introduction 393 8.1. A Distribution
Free Test for Independence Based on Signs (Kendall) 393 8.2. An Estimator Associated with the Kendall Statistic (Kendall) 413 8.3. An Asymptotically Distribution
Free Confidence Interval Based on the Kendall Statistic (Samara
Randles, Fligner
Rust, Noether) 415 8.4. An Asymptotically Distribution
Free Confidence Interval Based on Efron's Bootstrap 420 8.5. A Distribution
Free Test for Independence Based on Ranks (Spearman) 427 8.6. A Distribution
Free Test for Independence Against Broad Alternatives (Hoeffding) 442 8.7. Efficiencies of Independence Procedures 450 9. Regression Problems 451 Introduction 451 One Regression Line 452 9.1. A Distribution
Free Test for the Slope of the Regression Line (Theil) 452 9.2. A Slope Estimator Associated with the Theil Statistic (Theil) 458 9.3. A Distribution
Free Confidence Interval Associated with the Theil Test (Theil) 460 9.4. An Intercept Estimator Associated with the Theil Statistic and Use of the Estimated Linear Relationship for Prediction (Hettmansperger
McKean
Sheather) 463 k(>=2) Regression Lines 466 9.5. An Asymptotically Distribution
Free Test for the Parallelism of Several Regression Lines (Sen, Adichie) 466 General Multiple Linear Regression 475 9.6. Asymptotically Distribution
Free Rank
Based Tests for General Multiple Linear Regression (Jaeckel, Hettmansperger
McKean) 475 Nonparametric Regression Analysis 490 9.7. An Introduction to Non
Rank
Based Approaches to Nonparametric Regression Analysis 490 9.8. Efficiencies of Regression Procedures 494 10. Comparing Two Success Probabilities 495 Introduction 495 10.1. Approximate Tests and Confidence Intervals for the Difference between Two Success Probabilities (Pearson) 496 10.2. An Exact Test for the Difference between Two Success Probabilities (Fisher) 511 10.3. Inference for the Odds Ratio (Fisher, Cornfield) 515 10.4. Inference for k Strata of 2 × 2 Tables (Mantel and Haenszel) 522 10.5. Efficiencies 534 11. Life Distributions and Survival Analysis 535 Introduction 535 11.1. A Test of Exponentiality Versus IFR Alternatives (Epstein) 536 11.2. A Test of Exponentiality Versus NBU Alternatives (Hollander
Proschan) 545 11.3. A Test of Exponentiality Versus DMRL Alternatives (Hollander
Proschan) 555 11.4. A Test of Exponentiality Versus a Trend Change in Mean Residual Life (Guess
Hollander
Proschan) 563 11.5. A Confidence Band for the Distribution Function (Kolmogorov) 568 11.6. An Estimator of the Distribution Function When the Data are Censored (Kaplan
Meier) 578 11.7. A Two
Sample Test for Censored Data (Mantel) 594 11.8. Efficiencies 605 12. Density Estimation 609 Introduction 609 12.1. Density Functions and Histograms 609 12.2. Kernel Density Estimation 617 12.3. Bandwidth Selection 624 12.4. Other Methods 628 13. Wavelets 629 Introduction 629 13.1. Wavelet Representation of a Function 630 13.2. Wavelet Thresholding 644 13.3. Other Uses of Wavelets in Statistics 655 14. Smoothing 656 Introduction 656 14.1. Local Averaging (Friedman) 657 14.2. Local Regression (Cleveland) 662 14.3. Kernel Smoothing 667 14.4. Other Methods of Smoothing 675 15. Ranked Set Sampling 676 Introduction 676 15.1. Rationale and Historical Development 676 15.2. Collecting a Ranked Set Sample 677 15.3. Ranked Set Sampling Estimation of a Population Mean 685 15.4. Ranked Set Sample Analogs of the Mann
Whitney
Wilcoxon Two
Sample Procedures (Bohn
Wolfe) 717 15.5. Other Important Issues for Ranked Set Sampling 737 15.6. Extensions and Related Approaches 742 16. An Introduction to Bayesian Nonparametric Statistics via the Dirichlet Process 744 Introduction 744 16.1. Ferguson's Dirichlet Process 745 16.2. A Bayes Estimator of the Distribution Function (Ferguson) 749 16.3. Rank Order Estimation (Campbell and Hollander) 752 16.4. A Bayes Estimator of the Distribution When the Data are Right
Censored (Susarla and Van Ryzin) 755 16.5. Other Bayesian Approaches 759 Bibliography 763 R Program Index 791 Author Index 799 Subject Index 809
Free Property 2 1.3. Some Real
World Applications 3 1.4. Format and Organization 6 1.5. Computing with R 8 1.6. Historical Background 9 2. The Dichotomous Data Problem 11 Introduction 11 2.1. A Binomial Test 11 2.2. An Estimator for the Probability of Success 22 2.3. A Confidence Interval for the Probability of Success (Wilson) 24 2.4. Bayes Estimators for the Probability of Success 33 3. The One
Sample Location Problem 39 Introduction 39 Paired Replicates Analyses by Way of Signed Ranks 39 3.1. A Distribution
Free Signed Rank Test (Wilcoxon) 40 3.2. An Estimator Associated with Wilcoxon's Signed Rank Statistic (Hodges
Lehmann) 56 3.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Signed Rank Test (Tukey) 59 Paired Replicates Analyses by Way of Signs 63 3.4. A Distribution
Free Sign Test (Fisher) 63 3.5. An Estimator Associated with the Sign Statistic (Hodges
Lehmann) 76 3.6. A Distribution
Free Confidence Interval Based on the Sign Test (Thompson, Savur) 80 One
Sample Data 84 3.7. Procedures Based on the Signed Rank Statistic 84 3.8. Procedures Based on the Sign Statistic 90 3.9. An Asymptotically Distribution
Free Test of Symmetry (Randles
Fligner
Policello
Wolfe, Davis
Quade) 94 Bivariate Data 102 3.10. A Distribution
Free Test for Bivariate Symmetry (Hollander) 102 3.11. Efficiencies of Paired Replicates and One
Sample Location Procedures 112 4. The Two
Sample Location Problem 115 Introduction 115 4.1. A Distribution
Free Rank Sum Test (Wilcoxon, Mann and Whitney) 115 4.2. An Estimator Associated with Wilcoxon's Rank Sum Statistic (Hodges
Lehmann) 136 4.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Rank Sum Test (Moses) 142 4.4. A Robust Rank Test for the Behrens
Fisher Problem (Fligner
Policello) 145 4.5. Efficiencies of Two
Sample Location Procedures 149 5. The Two
Sample Dispersion Problem and Other Two
Sample Problems 151 Introduction 151 5.1. A Distribution
Free Rank Test for Dispersion
Medians Equal (Ansari
Bradley) 152 5.2. An Asymptotically Distribution
Free Test for Dispersion Based on the Jackknife
Medians Not Necessarily Equal (Miller) 169 5.3. A Distribution
Free Rank Test for Either Location or Dispersion (Lepage) 181 5.4. A Distribution
Free Test for General Differences in Two Populations (Kolmogorov
Smirnov) 190 5.5. Efficiencies of Two
Sample Dispersion and Broad Alternatives Procedures 200 6. The One
Way Layout 202 Introduction 202 6.1. A Distribution
Free Test for General Alternatives (Kruskal
Wallis) 204 6.2. A Distribution
Free Test for Ordered Alternatives (Jonckheere
Terpstra) 215 6.3. Distribution
Free Tests for Umbrella Alternatives (Mack
Wolfe) 225 6.3A. A Distribution
Free Test for Umbrella Alternatives, Peak Known (Mack
Wolfe) 226 6.3B. A Distribution
Free Test for Umbrella Alternatives, Peak Unknown (Mack
Wolfe) 241 6.4. A Distribution
Free Test for Treatments Versus a Control (Fligner
Wolfe) 249 Rationale For Multiple Comparison Procedures 255 6.5. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
General Configuration (Dwass, Steel, and Critchlow
Fligner) 256 6.6. Distribution
Free One
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
Ordered Treatment Effects (Hayter
Stone) 265 6.7. Distribution
Free One
Sided Treatments
Versus
Control Multiple Comparisons Based on Joint Rankings (Nemenyi, Damico
Wolfe) 271 6.8. Contrast Estimation Based on Hodges
Lehmann Two
Sample Estimators (Spjøtvoll) 278 6.9. Simultaneous Confidence Intervals for All Simple Contrasts (Critchlow
Fligner) 282 6.10. Efficiencies of One
Way Layout Procedures 287 7. The Two
Way Layout 289 Introduction 289 7.1. A Distribution
Free Test for General Alternatives in a Randomized Complete Block Design (Friedman, Kendall
Babington Smith) 292 7.2. A Distribution
Free Test for Ordered Alternatives in a Randomized Complete Block Design (Page) 304 Rationale for Multiple Comparison Procedures 315 7.3. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Friedman Rank Sums
General Configuration (Wilcoxon, Nemenyi, McDonald
Thompson) 316 7.4. Distribution
Free One
Sided Treatments Versus Control Multiple Comparisons Based on Friedman Rank Sums (Nemenyi, Wilcoxon
Wilcox, Miller) 322 7.5. Contrast Estimation Based on One
Sample Median Estimators (Doksum) 328 Incomplete Block Data
Two
Way Layout with Zero or One Observation Per Treatment
Block Combination 331 7.6. A Distribution
Free Test for General Alternatives in a Randomized Balanced Incomplete Block Design (BIBD) (Durbin
Skillings
Mack) 332 7.7. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for Balanced Incomplete Block Designs (Skillings
Mack) 341 7.8. A Distribution
Free Test for General Alternatives for Data From an Arbitrary Incomplete Block Design (Skillings
Mack) 343 Replications
Two
Way Layout with at Least One Observation for Every Treatment
Block Combination 354 7.9. A Distribution
Free Test for General Alternatives in a Randomized Block Design with an Equal Number c(>1) of Replications Per Treatment
Block Combination (Mack
Skillings) 354 7.10. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for a Two
Way Layout with an Equal Number of Replications in Each Treatment
Block Combination (Mack
Skillings) 367 Analyses Associated with Signed Ranks 370 7.11. A Test Based on Wilcoxon Signed Ranks for General Alternatives in a Randomized Complete Block Design (Doksum) 370 7.12. A Test Based on Wilcoxon Signed Ranks for Ordered Alternatives in a Randomized Complete Block Design (Hollander) 376 7.13. Approximate Two
Sided All
Treatments Multiple Comparisons Based on Signed Ranks (Nemenyi) 379 7.14. Approximate One
Sided Treatments
Versus
Control Multiple Comparisons Based on Signed Ranks (Hollander) 382 7.15. Contrast Estimation Based on the One
Sample Hodges
Lehmann Estimators (Lehmann) 386 7.16. Efficiencies of Two
Way Layout Procedures 390 8. The Independence Problem 393 Introduction 393 8.1. A Distribution
Free Test for Independence Based on Signs (Kendall) 393 8.2. An Estimator Associated with the Kendall Statistic (Kendall) 413 8.3. An Asymptotically Distribution
Free Confidence Interval Based on the Kendall Statistic (Samara
Randles, Fligner
Rust, Noether) 415 8.4. An Asymptotically Distribution
Free Confidence Interval Based on Efron's Bootstrap 420 8.5. A Distribution
Free Test for Independence Based on Ranks (Spearman) 427 8.6. A Distribution
Free Test for Independence Against Broad Alternatives (Hoeffding) 442 8.7. Efficiencies of Independence Procedures 450 9. Regression Problems 451 Introduction 451 One Regression Line 452 9.1. A Distribution
Free Test for the Slope of the Regression Line (Theil) 452 9.2. A Slope Estimator Associated with the Theil Statistic (Theil) 458 9.3. A Distribution
Free Confidence Interval Associated with the Theil Test (Theil) 460 9.4. An Intercept Estimator Associated with the Theil Statistic and Use of the Estimated Linear Relationship for Prediction (Hettmansperger
McKean
Sheather) 463 k(>=2) Regression Lines 466 9.5. An Asymptotically Distribution
Free Test for the Parallelism of Several Regression Lines (Sen, Adichie) 466 General Multiple Linear Regression 475 9.6. Asymptotically Distribution
Free Rank
Based Tests for General Multiple Linear Regression (Jaeckel, Hettmansperger
McKean) 475 Nonparametric Regression Analysis 490 9.7. An Introduction to Non
Rank
Based Approaches to Nonparametric Regression Analysis 490 9.8. Efficiencies of Regression Procedures 494 10. Comparing Two Success Probabilities 495 Introduction 495 10.1. Approximate Tests and Confidence Intervals for the Difference between Two Success Probabilities (Pearson) 496 10.2. An Exact Test for the Difference between Two Success Probabilities (Fisher) 511 10.3. Inference for the Odds Ratio (Fisher, Cornfield) 515 10.4. Inference for k Strata of 2 × 2 Tables (Mantel and Haenszel) 522 10.5. Efficiencies 534 11. Life Distributions and Survival Analysis 535 Introduction 535 11.1. A Test of Exponentiality Versus IFR Alternatives (Epstein) 536 11.2. A Test of Exponentiality Versus NBU Alternatives (Hollander
Proschan) 545 11.3. A Test of Exponentiality Versus DMRL Alternatives (Hollander
Proschan) 555 11.4. A Test of Exponentiality Versus a Trend Change in Mean Residual Life (Guess
Hollander
Proschan) 563 11.5. A Confidence Band for the Distribution Function (Kolmogorov) 568 11.6. An Estimator of the Distribution Function When the Data are Censored (Kaplan
Meier) 578 11.7. A Two
Sample Test for Censored Data (Mantel) 594 11.8. Efficiencies 605 12. Density Estimation 609 Introduction 609 12.1. Density Functions and Histograms 609 12.2. Kernel Density Estimation 617 12.3. Bandwidth Selection 624 12.4. Other Methods 628 13. Wavelets 629 Introduction 629 13.1. Wavelet Representation of a Function 630 13.2. Wavelet Thresholding 644 13.3. Other Uses of Wavelets in Statistics 655 14. Smoothing 656 Introduction 656 14.1. Local Averaging (Friedman) 657 14.2. Local Regression (Cleveland) 662 14.3. Kernel Smoothing 667 14.4. Other Methods of Smoothing 675 15. Ranked Set Sampling 676 Introduction 676 15.1. Rationale and Historical Development 676 15.2. Collecting a Ranked Set Sample 677 15.3. Ranked Set Sampling Estimation of a Population Mean 685 15.4. Ranked Set Sample Analogs of the Mann
Whitney
Wilcoxon Two
Sample Procedures (Bohn
Wolfe) 717 15.5. Other Important Issues for Ranked Set Sampling 737 15.6. Extensions and Related Approaches 742 16. An Introduction to Bayesian Nonparametric Statistics via the Dirichlet Process 744 Introduction 744 16.1. Ferguson's Dirichlet Process 745 16.2. A Bayes Estimator of the Distribution Function (Ferguson) 749 16.3. Rank Order Estimation (Campbell and Hollander) 752 16.4. A Bayes Estimator of the Distribution When the Data are Right
Censored (Susarla and Van Ryzin) 755 16.5. Other Bayesian Approaches 759 Bibliography 763 R Program Index 791 Author Index 799 Subject Index 809
Preface xiii 1. Introduction 1 1.1. Advantages of Nonparametric Methods 1 1.2. The Distribution
Free Property 2 1.3. Some Real
World Applications 3 1.4. Format and Organization 6 1.5. Computing with R 8 1.6. Historical Background 9 2. The Dichotomous Data Problem 11 Introduction 11 2.1. A Binomial Test 11 2.2. An Estimator for the Probability of Success 22 2.3. A Confidence Interval for the Probability of Success (Wilson) 24 2.4. Bayes Estimators for the Probability of Success 33 3. The One
Sample Location Problem 39 Introduction 39 Paired Replicates Analyses by Way of Signed Ranks 39 3.1. A Distribution
Free Signed Rank Test (Wilcoxon) 40 3.2. An Estimator Associated with Wilcoxon's Signed Rank Statistic (Hodges
Lehmann) 56 3.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Signed Rank Test (Tukey) 59 Paired Replicates Analyses by Way of Signs 63 3.4. A Distribution
Free Sign Test (Fisher) 63 3.5. An Estimator Associated with the Sign Statistic (Hodges
Lehmann) 76 3.6. A Distribution
Free Confidence Interval Based on the Sign Test (Thompson, Savur) 80 One
Sample Data 84 3.7. Procedures Based on the Signed Rank Statistic 84 3.8. Procedures Based on the Sign Statistic 90 3.9. An Asymptotically Distribution
Free Test of Symmetry (Randles
Fligner
Policello
Wolfe, Davis
Quade) 94 Bivariate Data 102 3.10. A Distribution
Free Test for Bivariate Symmetry (Hollander) 102 3.11. Efficiencies of Paired Replicates and One
Sample Location Procedures 112 4. The Two
Sample Location Problem 115 Introduction 115 4.1. A Distribution
Free Rank Sum Test (Wilcoxon, Mann and Whitney) 115 4.2. An Estimator Associated with Wilcoxon's Rank Sum Statistic (Hodges
Lehmann) 136 4.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Rank Sum Test (Moses) 142 4.4. A Robust Rank Test for the Behrens
Fisher Problem (Fligner
Policello) 145 4.5. Efficiencies of Two
Sample Location Procedures 149 5. The Two
Sample Dispersion Problem and Other Two
Sample Problems 151 Introduction 151 5.1. A Distribution
Free Rank Test for Dispersion
Medians Equal (Ansari
Bradley) 152 5.2. An Asymptotically Distribution
Free Test for Dispersion Based on the Jackknife
Medians Not Necessarily Equal (Miller) 169 5.3. A Distribution
Free Rank Test for Either Location or Dispersion (Lepage) 181 5.4. A Distribution
Free Test for General Differences in Two Populations (Kolmogorov
Smirnov) 190 5.5. Efficiencies of Two
Sample Dispersion and Broad Alternatives Procedures 200 6. The One
Way Layout 202 Introduction 202 6.1. A Distribution
Free Test for General Alternatives (Kruskal
Wallis) 204 6.2. A Distribution
Free Test for Ordered Alternatives (Jonckheere
Terpstra) 215 6.3. Distribution
Free Tests for Umbrella Alternatives (Mack
Wolfe) 225 6.3A. A Distribution
Free Test for Umbrella Alternatives, Peak Known (Mack
Wolfe) 226 6.3B. A Distribution
Free Test for Umbrella Alternatives, Peak Unknown (Mack
Wolfe) 241 6.4. A Distribution
Free Test for Treatments Versus a Control (Fligner
Wolfe) 249 Rationale For Multiple Comparison Procedures 255 6.5. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
General Configuration (Dwass, Steel, and Critchlow
Fligner) 256 6.6. Distribution
Free One
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
Ordered Treatment Effects (Hayter
Stone) 265 6.7. Distribution
Free One
Sided Treatments
Versus
Control Multiple Comparisons Based on Joint Rankings (Nemenyi, Damico
Wolfe) 271 6.8. Contrast Estimation Based on Hodges
Lehmann Two
Sample Estimators (Spjøtvoll) 278 6.9. Simultaneous Confidence Intervals for All Simple Contrasts (Critchlow
Fligner) 282 6.10. Efficiencies of One
Way Layout Procedures 287 7. The Two
Way Layout 289 Introduction 289 7.1. A Distribution
Free Test for General Alternatives in a Randomized Complete Block Design (Friedman, Kendall
Babington Smith) 292 7.2. A Distribution
Free Test for Ordered Alternatives in a Randomized Complete Block Design (Page) 304 Rationale for Multiple Comparison Procedures 315 7.3. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Friedman Rank Sums
General Configuration (Wilcoxon, Nemenyi, McDonald
Thompson) 316 7.4. Distribution
Free One
Sided Treatments Versus Control Multiple Comparisons Based on Friedman Rank Sums (Nemenyi, Wilcoxon
Wilcox, Miller) 322 7.5. Contrast Estimation Based on One
Sample Median Estimators (Doksum) 328 Incomplete Block Data
Two
Way Layout with Zero or One Observation Per Treatment
Block Combination 331 7.6. A Distribution
Free Test for General Alternatives in a Randomized Balanced Incomplete Block Design (BIBD) (Durbin
Skillings
Mack) 332 7.7. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for Balanced Incomplete Block Designs (Skillings
Mack) 341 7.8. A Distribution
Free Test for General Alternatives for Data From an Arbitrary Incomplete Block Design (Skillings
Mack) 343 Replications
Two
Way Layout with at Least One Observation for Every Treatment
Block Combination 354 7.9. A Distribution
Free Test for General Alternatives in a Randomized Block Design with an Equal Number c(>1) of Replications Per Treatment
Block Combination (Mack
Skillings) 354 7.10. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for a Two
Way Layout with an Equal Number of Replications in Each Treatment
Block Combination (Mack
Skillings) 367 Analyses Associated with Signed Ranks 370 7.11. A Test Based on Wilcoxon Signed Ranks for General Alternatives in a Randomized Complete Block Design (Doksum) 370 7.12. A Test Based on Wilcoxon Signed Ranks for Ordered Alternatives in a Randomized Complete Block Design (Hollander) 376 7.13. Approximate Two
Sided All
Treatments Multiple Comparisons Based on Signed Ranks (Nemenyi) 379 7.14. Approximate One
Sided Treatments
Versus
Control Multiple Comparisons Based on Signed Ranks (Hollander) 382 7.15. Contrast Estimation Based on the One
Sample Hodges
Lehmann Estimators (Lehmann) 386 7.16. Efficiencies of Two
Way Layout Procedures 390 8. The Independence Problem 393 Introduction 393 8.1. A Distribution
Free Test for Independence Based on Signs (Kendall) 393 8.2. An Estimator Associated with the Kendall Statistic (Kendall) 413 8.3. An Asymptotically Distribution
Free Confidence Interval Based on the Kendall Statistic (Samara
Randles, Fligner
Rust, Noether) 415 8.4. An Asymptotically Distribution
Free Confidence Interval Based on Efron's Bootstrap 420 8.5. A Distribution
Free Test for Independence Based on Ranks (Spearman) 427 8.6. A Distribution
Free Test for Independence Against Broad Alternatives (Hoeffding) 442 8.7. Efficiencies of Independence Procedures 450 9. Regression Problems 451 Introduction 451 One Regression Line 452 9.1. A Distribution
Free Test for the Slope of the Regression Line (Theil) 452 9.2. A Slope Estimator Associated with the Theil Statistic (Theil) 458 9.3. A Distribution
Free Confidence Interval Associated with the Theil Test (Theil) 460 9.4. An Intercept Estimator Associated with the Theil Statistic and Use of the Estimated Linear Relationship for Prediction (Hettmansperger
McKean
Sheather) 463 k(>=2) Regression Lines 466 9.5. An Asymptotically Distribution
Free Test for the Parallelism of Several Regression Lines (Sen, Adichie) 466 General Multiple Linear Regression 475 9.6. Asymptotically Distribution
Free Rank
Based Tests for General Multiple Linear Regression (Jaeckel, Hettmansperger
McKean) 475 Nonparametric Regression Analysis 490 9.7. An Introduction to Non
Rank
Based Approaches to Nonparametric Regression Analysis 490 9.8. Efficiencies of Regression Procedures 494 10. Comparing Two Success Probabilities 495 Introduction 495 10.1. Approximate Tests and Confidence Intervals for the Difference between Two Success Probabilities (Pearson) 496 10.2. An Exact Test for the Difference between Two Success Probabilities (Fisher) 511 10.3. Inference for the Odds Ratio (Fisher, Cornfield) 515 10.4. Inference for k Strata of 2 × 2 Tables (Mantel and Haenszel) 522 10.5. Efficiencies 534 11. Life Distributions and Survival Analysis 535 Introduction 535 11.1. A Test of Exponentiality Versus IFR Alternatives (Epstein) 536 11.2. A Test of Exponentiality Versus NBU Alternatives (Hollander
Proschan) 545 11.3. A Test of Exponentiality Versus DMRL Alternatives (Hollander
Proschan) 555 11.4. A Test of Exponentiality Versus a Trend Change in Mean Residual Life (Guess
Hollander
Proschan) 563 11.5. A Confidence Band for the Distribution Function (Kolmogorov) 568 11.6. An Estimator of the Distribution Function When the Data are Censored (Kaplan
Meier) 578 11.7. A Two
Sample Test for Censored Data (Mantel) 594 11.8. Efficiencies 605 12. Density Estimation 609 Introduction 609 12.1. Density Functions and Histograms 609 12.2. Kernel Density Estimation 617 12.3. Bandwidth Selection 624 12.4. Other Methods 628 13. Wavelets 629 Introduction 629 13.1. Wavelet Representation of a Function 630 13.2. Wavelet Thresholding 644 13.3. Other Uses of Wavelets in Statistics 655 14. Smoothing 656 Introduction 656 14.1. Local Averaging (Friedman) 657 14.2. Local Regression (Cleveland) 662 14.3. Kernel Smoothing 667 14.4. Other Methods of Smoothing 675 15. Ranked Set Sampling 676 Introduction 676 15.1. Rationale and Historical Development 676 15.2. Collecting a Ranked Set Sample 677 15.3. Ranked Set Sampling Estimation of a Population Mean 685 15.4. Ranked Set Sample Analogs of the Mann
Whitney
Wilcoxon Two
Sample Procedures (Bohn
Wolfe) 717 15.5. Other Important Issues for Ranked Set Sampling 737 15.6. Extensions and Related Approaches 742 16. An Introduction to Bayesian Nonparametric Statistics via the Dirichlet Process 744 Introduction 744 16.1. Ferguson's Dirichlet Process 745 16.2. A Bayes Estimator of the Distribution Function (Ferguson) 749 16.3. Rank Order Estimation (Campbell and Hollander) 752 16.4. A Bayes Estimator of the Distribution When the Data are Right
Censored (Susarla and Van Ryzin) 755 16.5. Other Bayesian Approaches 759 Bibliography 763 R Program Index 791 Author Index 799 Subject Index 809
Free Property 2 1.3. Some Real
World Applications 3 1.4. Format and Organization 6 1.5. Computing with R 8 1.6. Historical Background 9 2. The Dichotomous Data Problem 11 Introduction 11 2.1. A Binomial Test 11 2.2. An Estimator for the Probability of Success 22 2.3. A Confidence Interval for the Probability of Success (Wilson) 24 2.4. Bayes Estimators for the Probability of Success 33 3. The One
Sample Location Problem 39 Introduction 39 Paired Replicates Analyses by Way of Signed Ranks 39 3.1. A Distribution
Free Signed Rank Test (Wilcoxon) 40 3.2. An Estimator Associated with Wilcoxon's Signed Rank Statistic (Hodges
Lehmann) 56 3.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Signed Rank Test (Tukey) 59 Paired Replicates Analyses by Way of Signs 63 3.4. A Distribution
Free Sign Test (Fisher) 63 3.5. An Estimator Associated with the Sign Statistic (Hodges
Lehmann) 76 3.6. A Distribution
Free Confidence Interval Based on the Sign Test (Thompson, Savur) 80 One
Sample Data 84 3.7. Procedures Based on the Signed Rank Statistic 84 3.8. Procedures Based on the Sign Statistic 90 3.9. An Asymptotically Distribution
Free Test of Symmetry (Randles
Fligner
Policello
Wolfe, Davis
Quade) 94 Bivariate Data 102 3.10. A Distribution
Free Test for Bivariate Symmetry (Hollander) 102 3.11. Efficiencies of Paired Replicates and One
Sample Location Procedures 112 4. The Two
Sample Location Problem 115 Introduction 115 4.1. A Distribution
Free Rank Sum Test (Wilcoxon, Mann and Whitney) 115 4.2. An Estimator Associated with Wilcoxon's Rank Sum Statistic (Hodges
Lehmann) 136 4.3. A Distribution
Free Confidence Interval Based on Wilcoxon's Rank Sum Test (Moses) 142 4.4. A Robust Rank Test for the Behrens
Fisher Problem (Fligner
Policello) 145 4.5. Efficiencies of Two
Sample Location Procedures 149 5. The Two
Sample Dispersion Problem and Other Two
Sample Problems 151 Introduction 151 5.1. A Distribution
Free Rank Test for Dispersion
Medians Equal (Ansari
Bradley) 152 5.2. An Asymptotically Distribution
Free Test for Dispersion Based on the Jackknife
Medians Not Necessarily Equal (Miller) 169 5.3. A Distribution
Free Rank Test for Either Location or Dispersion (Lepage) 181 5.4. A Distribution
Free Test for General Differences in Two Populations (Kolmogorov
Smirnov) 190 5.5. Efficiencies of Two
Sample Dispersion and Broad Alternatives Procedures 200 6. The One
Way Layout 202 Introduction 202 6.1. A Distribution
Free Test for General Alternatives (Kruskal
Wallis) 204 6.2. A Distribution
Free Test for Ordered Alternatives (Jonckheere
Terpstra) 215 6.3. Distribution
Free Tests for Umbrella Alternatives (Mack
Wolfe) 225 6.3A. A Distribution
Free Test for Umbrella Alternatives, Peak Known (Mack
Wolfe) 226 6.3B. A Distribution
Free Test for Umbrella Alternatives, Peak Unknown (Mack
Wolfe) 241 6.4. A Distribution
Free Test for Treatments Versus a Control (Fligner
Wolfe) 249 Rationale For Multiple Comparison Procedures 255 6.5. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
General Configuration (Dwass, Steel, and Critchlow
Fligner) 256 6.6. Distribution
Free One
Sided All
Treatments Multiple Comparisons Based on Pairwise Rankings
Ordered Treatment Effects (Hayter
Stone) 265 6.7. Distribution
Free One
Sided Treatments
Versus
Control Multiple Comparisons Based on Joint Rankings (Nemenyi, Damico
Wolfe) 271 6.8. Contrast Estimation Based on Hodges
Lehmann Two
Sample Estimators (Spjøtvoll) 278 6.9. Simultaneous Confidence Intervals for All Simple Contrasts (Critchlow
Fligner) 282 6.10. Efficiencies of One
Way Layout Procedures 287 7. The Two
Way Layout 289 Introduction 289 7.1. A Distribution
Free Test for General Alternatives in a Randomized Complete Block Design (Friedman, Kendall
Babington Smith) 292 7.2. A Distribution
Free Test for Ordered Alternatives in a Randomized Complete Block Design (Page) 304 Rationale for Multiple Comparison Procedures 315 7.3. Distribution
Free Two
Sided All
Treatments Multiple Comparisons Based on Friedman Rank Sums
General Configuration (Wilcoxon, Nemenyi, McDonald
Thompson) 316 7.4. Distribution
Free One
Sided Treatments Versus Control Multiple Comparisons Based on Friedman Rank Sums (Nemenyi, Wilcoxon
Wilcox, Miller) 322 7.5. Contrast Estimation Based on One
Sample Median Estimators (Doksum) 328 Incomplete Block Data
Two
Way Layout with Zero or One Observation Per Treatment
Block Combination 331 7.6. A Distribution
Free Test for General Alternatives in a Randomized Balanced Incomplete Block Design (BIBD) (Durbin
Skillings
Mack) 332 7.7. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for Balanced Incomplete Block Designs (Skillings
Mack) 341 7.8. A Distribution
Free Test for General Alternatives for Data From an Arbitrary Incomplete Block Design (Skillings
Mack) 343 Replications
Two
Way Layout with at Least One Observation for Every Treatment
Block Combination 354 7.9. A Distribution
Free Test for General Alternatives in a Randomized Block Design with an Equal Number c(>1) of Replications Per Treatment
Block Combination (Mack
Skillings) 354 7.10. Asymptotically Distribution
Free Two
Sided All
Treatments Multiple Comparisons for a Two
Way Layout with an Equal Number of Replications in Each Treatment
Block Combination (Mack
Skillings) 367 Analyses Associated with Signed Ranks 370 7.11. A Test Based on Wilcoxon Signed Ranks for General Alternatives in a Randomized Complete Block Design (Doksum) 370 7.12. A Test Based on Wilcoxon Signed Ranks for Ordered Alternatives in a Randomized Complete Block Design (Hollander) 376 7.13. Approximate Two
Sided All
Treatments Multiple Comparisons Based on Signed Ranks (Nemenyi) 379 7.14. Approximate One
Sided Treatments
Versus
Control Multiple Comparisons Based on Signed Ranks (Hollander) 382 7.15. Contrast Estimation Based on the One
Sample Hodges
Lehmann Estimators (Lehmann) 386 7.16. Efficiencies of Two
Way Layout Procedures 390 8. The Independence Problem 393 Introduction 393 8.1. A Distribution
Free Test for Independence Based on Signs (Kendall) 393 8.2. An Estimator Associated with the Kendall Statistic (Kendall) 413 8.3. An Asymptotically Distribution
Free Confidence Interval Based on the Kendall Statistic (Samara
Randles, Fligner
Rust, Noether) 415 8.4. An Asymptotically Distribution
Free Confidence Interval Based on Efron's Bootstrap 420 8.5. A Distribution
Free Test for Independence Based on Ranks (Spearman) 427 8.6. A Distribution
Free Test for Independence Against Broad Alternatives (Hoeffding) 442 8.7. Efficiencies of Independence Procedures 450 9. Regression Problems 451 Introduction 451 One Regression Line 452 9.1. A Distribution
Free Test for the Slope of the Regression Line (Theil) 452 9.2. A Slope Estimator Associated with the Theil Statistic (Theil) 458 9.3. A Distribution
Free Confidence Interval Associated with the Theil Test (Theil) 460 9.4. An Intercept Estimator Associated with the Theil Statistic and Use of the Estimated Linear Relationship for Prediction (Hettmansperger
McKean
Sheather) 463 k(>=2) Regression Lines 466 9.5. An Asymptotically Distribution
Free Test for the Parallelism of Several Regression Lines (Sen, Adichie) 466 General Multiple Linear Regression 475 9.6. Asymptotically Distribution
Free Rank
Based Tests for General Multiple Linear Regression (Jaeckel, Hettmansperger
McKean) 475 Nonparametric Regression Analysis 490 9.7. An Introduction to Non
Rank
Based Approaches to Nonparametric Regression Analysis 490 9.8. Efficiencies of Regression Procedures 494 10. Comparing Two Success Probabilities 495 Introduction 495 10.1. Approximate Tests and Confidence Intervals for the Difference between Two Success Probabilities (Pearson) 496 10.2. An Exact Test for the Difference between Two Success Probabilities (Fisher) 511 10.3. Inference for the Odds Ratio (Fisher, Cornfield) 515 10.4. Inference for k Strata of 2 × 2 Tables (Mantel and Haenszel) 522 10.5. Efficiencies 534 11. Life Distributions and Survival Analysis 535 Introduction 535 11.1. A Test of Exponentiality Versus IFR Alternatives (Epstein) 536 11.2. A Test of Exponentiality Versus NBU Alternatives (Hollander
Proschan) 545 11.3. A Test of Exponentiality Versus DMRL Alternatives (Hollander
Proschan) 555 11.4. A Test of Exponentiality Versus a Trend Change in Mean Residual Life (Guess
Hollander
Proschan) 563 11.5. A Confidence Band for the Distribution Function (Kolmogorov) 568 11.6. An Estimator of the Distribution Function When the Data are Censored (Kaplan
Meier) 578 11.7. A Two
Sample Test for Censored Data (Mantel) 594 11.8. Efficiencies 605 12. Density Estimation 609 Introduction 609 12.1. Density Functions and Histograms 609 12.2. Kernel Density Estimation 617 12.3. Bandwidth Selection 624 12.4. Other Methods 628 13. Wavelets 629 Introduction 629 13.1. Wavelet Representation of a Function 630 13.2. Wavelet Thresholding 644 13.3. Other Uses of Wavelets in Statistics 655 14. Smoothing 656 Introduction 656 14.1. Local Averaging (Friedman) 657 14.2. Local Regression (Cleveland) 662 14.3. Kernel Smoothing 667 14.4. Other Methods of Smoothing 675 15. Ranked Set Sampling 676 Introduction 676 15.1. Rationale and Historical Development 676 15.2. Collecting a Ranked Set Sample 677 15.3. Ranked Set Sampling Estimation of a Population Mean 685 15.4. Ranked Set Sample Analogs of the Mann
Whitney
Wilcoxon Two
Sample Procedures (Bohn
Wolfe) 717 15.5. Other Important Issues for Ranked Set Sampling 737 15.6. Extensions and Related Approaches 742 16. An Introduction to Bayesian Nonparametric Statistics via the Dirichlet Process 744 Introduction 744 16.1. Ferguson's Dirichlet Process 745 16.2. A Bayes Estimator of the Distribution Function (Ferguson) 749 16.3. Rank Order Estimation (Campbell and Hollander) 752 16.4. A Bayes Estimator of the Distribution When the Data are Right
Censored (Susarla and Van Ryzin) 755 16.5. Other Bayesian Approaches 759 Bibliography 763 R Program Index 791 Author Index 799 Subject Index 809