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Pragmatics of Uncertainty [Kõva köide]

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(Carnegie Mellon University, Pittsburgh, Pennsylvania, USA)
  • Formaat: Hardback, 352 pages, kõrgus x laius: 254x178 mm, kaal: 816 g, 69 Tables, black and white; 64 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Texts in Statistical Science
  • Ilmumisaeg: 27-Sep-2016
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1498719848
  • ISBN-13: 9781498719841
Teised raamatud teemal:
Pragmatics of UncertaintySuurem pilt
  • Formaat: Hardback, 352 pages, kõrgus x laius: 254x178 mm, kaal: 816 g, 69 Tables, black and white; 64 Illustrations, black and white
  • Sari: Chapman & Hall/CRC Texts in Statistical Science
  • Ilmumisaeg: 27-Sep-2016
  • Kirjastus: Chapman & Hall/CRC
  • ISBN-10: 1498719848
  • ISBN-13: 9781498719841
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781498719841.html
Märksõnad:

A fair question to ask of an advocate of subjective Bayesianism (which the author is) is "how would you model uncertainty " In this book, the author writes about how he has done it using real problems from the past, and offers additional comments about the context in which he was working.

Foreword xv
Preface xvii
1 Bayesian Paleoethnobotany (1988) 1(26)
Foreword
1(2)
Published Paper
3(1)
1.1 Styles of Data Analysis
3(1)
1.2 The Data
3(3)
1.3 Research Plan
6(2)
1.4 Prior Probabilities of Activities
8(5)
1.5 Botanical Remains: The Likelihood Function
13(2)
1.6 Computation of Posterior Distributions
15(2)
1.7 Conclusion
17(5)
References
22(1)
Discussion
23(1)
Reply to the Discussion
24(1)
Epilogue
25(1)
Teaching Suggestions
26(1)
2 Statistical Sampling in Tax Audits (1988) 27(26)
Foreword
27(2)
Published Paper
29(1)
2.1 Introduction
29(1)
2.2 The Theory of Statistical Sampling: An Overview
30(2)
2.3 Judicial Decisions
32(7)
2.4 The Case for Statistical Samples
39(2)
2.5 Statutory Standards for the Use of Statistical Sampling
41(8)
2.6 Conclusions
49(1)
Appendix A
49(1)
Epilogue
50(1)
Teaching Suggestions
51(2)
3 A Statistical Analysis of Adverse Impact of Employer Decisions (1990) 53(18)
Foreword
53(2)
Published Paper
55(1)
3.1 Introduction
55(1)
3.2 Database Issues
56(1)
3.3 Analyses
57(11)
3.3.1 Fisher's Exact Tests
58(2)
3.3.2 A Bayesian Analysis
60(6)
3.3.3 Paired Observations
66(2)
3.4 Conclusions
68(1)
References
68(1)
Epilogue
69(1)
Teaching Suggestions
70(1)
4 Subjective Bayesian Analysis for Surveys with Missing Data (1993) 71(18)
Foreword
71(2)
Published Paper
73(1)
4.1 Introduction
73(1)
4.2 Background and Analysis
74(8)
4.3 Conclusions
82(2)
References
84(2)
Epilogue
86(1)
Teaching Suggestions
86(3)
5 Missing Data in the Forensic Context (1997) 89(10)
Foreword
89(2)
Published Paper
91(1)
5.1 Introduction
91(1)
5.2 The New Jersey Turnpike Case
91(4)
5.3 Presentation to Court of Surveys with Missing Data
95(1)
References
96(1)
Epilogue
97(1)
Teaching Suggestions
97(2)
6 Bayesian Demography: Projecting the Iraqi Kurdish Population, 1977-1990 (1997) 99(26)
Foreword
99(2)
Published Paper
101(1)
6.1 Introduction
101(2)
6.2 Current Practices
103(3)
6.3 The Iraqi Kurdish Population
106(2)
6.4 Overview of Projection Procedure
108(1)
6.5 Projecting the Iraqi Kurdish Population
108(8)
6.5.1 Fertility
108(3)
6.5.2 Mortality
111(3)
6.5.3 Migration
114(1)
6.5.4 Obtaining a Base Population
114(2)
6.6 Results
116(4)
6.7 Discussion
120(1)
References
120(2)
Epilogue
122(1)
Teaching Suggestions
123(2)
7 An Allegation of Examination Copying (1999) 125(12)
Foreword
125(2)
Published Paper
127(1)
7.1 Data and Formal Analysis
127(1)
7.2 Priors: What to Look For
128(1)
7.3 An Index
128(1)
7.4 Results
129(3)
7.5 Conclusion
132(1)
7.6 Other Purposes, Other Indices
133(1)
References
134(1)
Epilogue
134(1)
Teaching Suggestions
134(3)
8 Vote Tampering in a District Justice Election in Beaver County, PA (2001) 137(20)
Foreword
137(2)
Published Paper
139(1)
8.1 Introduction
139(2)
8.2 Legal History
141(1)
8.3 Model
142(6)
8.3.1 Data Structuring
143(1)
8.3.2 Model Specification
143(4)
8.3.3 Estimation with Markov Chain Monte Carlo
147(1)
8.4 Results
148(3)
8.4.1 Model Validation
150(1)
8.5 Discussion
151(1)
Appendix
152(2)
References
154(1)
Epilogue
154(1)
Teaching Suggestions
155(2)
9 The Effect of Intensity of Effort to Reach Survey Respondents: A Toronto Smoking Survey (2001) 157(22)
Foreword
157(2)
Published Paper
159(1)
9.1 Introduction
159(1)
9.2 The Survey
160(1)
9.3 Overview of Methodology
161(1)
9.4 MAR Models
162(1)
9.4.1 Logistic Regression
162(1)
9.4.2 Bayesian Logistic Regression
163(1)
9.5 NI Model
163(6)
9.5.1 Modeling the Non-Response Mechanism
163(3)
9.5.2 Relating Non-Response to the Dependent Variable - The NI Model
166(1)
9.5.3 Data Augmentation
167(1)
9.5.4 Sampling from the Posterior Distribution
168(1)
9.6 Choice of Prior Distributions
169(1)
9.7 Results
170(3)
9.7.1 Coefficients for the Number of Calls
170(1)
9.7.2 Sensitivity to Priors
170(1)
9.7.3 Effect on Odds of Response
171(2)
9.7.4 Effect on Probability of Response
173(1)
9.8 Conclusion
173(1)
Appendices
174(1)
References
175(1)
Epilogue
176(1)
Teaching Suggestions
177(2)
10 Comparing Harm Done by Mobility and Class Absence: Missing Students and Missing Data (2003) 179(22)
Foreword
179(2)
Published Paper
181(1)
10.1 Introduction
181(1)
10.2 Data
182(3)
10.2.1 Data Description
182(2)
10.2.2 Missing Data
184(1)
10.3 Model Specification
185(4)
10.3.1 Notation
185(1)
10.3.2 Likelihood without Choice Indicators
185(2)
10.3.3 Likelihood with Choice Indicators
187(1)
10.3.4 Prior Distributions
188(1)
10.4 Methodology for Sampling from the Posterior Distribution
189(1)
10.5 Results
189(3)
10.6 Conclusions
192(2)
10.7 Discussion
194(1)
Appendix
194(1)
References
195(2)
Editor's Foreword
197(1)
Comment
198(1)
Epilogue
199(1)
Teaching Suggestions
200(1)
11 Hierarchical Models for Employment Decisions (2004) 201(26)
Foreword
201(2)
Published Paper
203(1)
11.1 Introduction
203(2)
11.2 Proportional Hazards Models
205(6)
11.2.1 Hierarchical Priors for Time Varying Coefficients
207(1)
11.2.2 Smoothness Priors
208(1)
11.2.3 Forming an Opinion about Smoothness
208(1)
11.2.4 Posterior Distribution
209(1)
11.2.5 Reexpressing β
210(1)
11.3 Examples
211(11)
11.3.1 Case K
211(6)
11.3.2 Case W
217(4)
11.3.3 Valentino v. United States Postal Service
221(1)
11.4 Discussion
222(2)
References
224(1)
Epilogue
225(1)
Teaching Suggestions
225(2)
12 Age- and Time-Varying Proportional Hazards Models for Employment Discrimination (2010) 227(20)
Foreword
227(2)
Published Paper
229(1)
12.1 Introduction
229(1)
12.2 Proportional Hazards Regression
230(5)
12.2.1 Overview
231(1)
12.2.2 Proportional Hazards Models for Time to Event Data
231(2)
12.2.3 Thin-Plate Spline Smoothness Priors
233(2)
12.3 Case W Revisited
235(8)
12.3.1 Forming an Opinion about Smoothness and Anisotropy
236(1)
12.3.2 Computing the Posterior Distribution
237(1)
12.3.3 Sensitivity Analysis
238(1)
12.3.4 Identification of the Anisotropy Parameter
239(1)
12.3.5 Previous Analyses of Case W
240(2)
12.3.6 Summary
242(1)
12.4 Discussion
243(1)
References
244(1)
Epilogue
245(1)
Teaching Suggestions
245(2)
13 Error Analysis for Small Angle Neutron Scattering Datasets Using Bayesian Inference {2010) 247(36)
Foreword
247(2)
Published Paper
249(1)
13.1 Introduction
249(6)
13.1.1 Correlation Lengths
252(2)
13.1.2 Small-angle Neutron Scattering
254(1)
13.2 The SANS Instrument
255(3)
13.2.1 Instrument Components
255(2)
13.2.2 Instrument Configurations
257(1)
13.3 SANS Error Analysis
258(8)
13.3.1 Traditional Error Analysis
258(1)
13.3.2 The Bayesian Alternative
259(7)
13.4 Results and Discussion
266(5)
13.4.1 Separate Marginal Distributions on ξL and ξS
268(1)
13.4.2 Joint Posterior Distribution on (ξL,ξS)
268(2)
13.4.3 Representing Fits Graphically: "family of curves" and Standardized Residual Distributions
270(1)
13.5 Conclusions
271(1)
Appendix A
272(1)
Appendix B
273(1)
References
274(1)
Comment
275(2)
Comment
277(1)
Rejoinder
278(2)
Epilogue
280(1)
Teaching Suggestions
280(3)
14 Impacts of Beliefs about Tropical Cyclone Detection on Conclusions about Trends in Tropical Cyclone Number (2011) 283(22)
Foreword
283(2)
Published Paper
285(1)
14.1 Introduction
285(2)
14.2 TC Detection and Recording over the Years
287(2)
14.3 Combining Detection Probability with Raw Counts
289(2)
14.4 Illustration
291(2)
14.5 Sensitivity to Prior Quantification
293(4)
14.6 Concluding Remarks
297(2)
14.6.1 Resolving Ambiguity with Further Studies
297(1)
14.6.2 Sensitivity to Formulation
297(1)
14.6.3 Toward a Flexible Formulation
298(1)
14.6.4 Incorporating Climate Models
298(1)
References
299(3)
Epilogue
302(1)
Teaching Suggestions
303(2)
15 The Number of Killings in Southern Rural Norway, 1300-1569 (2013) 305(16)
Foreword
305(2)
Published Paper
307(1)
15.1 Norwegian Homicide Law and the Documentary Evidence
307(1)
15.2 Demographic Evidence about the Number of Killings
308(1)
15.3 Models of the Data
309(8)
15.4 Conclusion
317(1)
References
318(1)
Epilogue
318(1)
Teaching Suggestions
319(2)
Epilogue 321(2)
Index 323(6)
Index of Names 329
Dr. Polhemus is Chief Technology Officer for Statpoint Technologies, Inc. and directs the development of STATGRAPHICS. He received his B.S.E. and Ph.D. degrees from the School of Engineering and Applied Science at Princeton University, under the tutelage of Dr. J. Stuart Hunter. Dr. Polhemus spent two years as an assistant professor in the Graduate School of Business Administration at the University of North Carolina at Chapel Hill and six years as an assistant professor in the Engineering School at Princeton University.Dr. Polhemus founded Statistical Graphics Corporation in 1980 to develop and promote the STATGRAPHICS software program. In 1983, he founded Strategy Plus, Inc., which developed EXECUSTAT for DOS. Dr. Polhemus founded NWP Associates, Inc., in 1993 to develop STATLETS, a set of Java applets which permit statistical data analysis over the Internet. In 1999 development of STATGRAPHICS was assumed by Statpoint Technologies, Inc.Dr. Polhemus lives in northern Virginia with his wife Caroline and is the proud father of four sons: Christopher, Gregory, Leland, and Michael.