The Resource Partial Identification of Probability Distributions, by Charles F. Manski, (electronic resource)

# Partial Identification of Probability Distributions, by Charles F. Manski, (electronic resource) Resource Information The item Partial Identification of Probability Distributions, by Charles F. Manski, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Oklahoma Libraries.This item is available to borrow from all library branches.

Label
Partial Identification of Probability Distributions
Title
Partial Identification of Probability Distributions
Statement of responsibility
by Charles F. Manski
Creator
Author
Author
Subject
Language
• eng
• eng
Summary
Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process. Statistical theory has revealed much about how strength of assumptions affects the precision of point estimates, but has had much less to say about how it affects the identification of population parameters. Indeed, it has been commonplace to think of identification as a binary event – a parameter is either identified or not – and to view point identification as a pre-condition for inference. Yet there is enormous scope for fruitful inference using data and assumptions that partially identify population parameters. This book explains why and shows how. The book presents in a rigorous and thorough manner the main elements of Charles Manski’s research on partial identification of probability distributions. One focus is prediction with missing outcome or covariate data. Another is decomposition of finite mixtures, with application to the analysis of contaminated sampling and ecological inference. A third major focus is the analysis of treatment response. Whatever the particular subject under study, the presentation follows a common path. The author first specifies the sampling process generating the available data and asks what may be learned about population parameters using the empirical evidence alone. He then ask how the (typically) setvalued identification regions for these parameters shrink if various assumptions are imposed. The approach to inference that runs throughout the book is deliberately conservative and thoroughly nonparametric. Conservative nonparametric analysis enables researchers to learn from the available data without imposing untenable assumptions. It enables establishment of a domain of consensus among researchers who may hold disparate beliefs about what assumptions are appropriate. Charles F. Manski is Board of Trustees Professor at Northwestern University. He is author of Identification Problems in the Social Sciences and Analog Estimation Methods in Econometrics. He is a Fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, and the Econometric Society
Member of
http://library.link/vocab/creatorName
Manski, Charles F
Dewey number
519.2/4
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
zxFyh3Ahzz8
Language note
English
LC call number
QA276-280
Literary form
non fiction
Nature of contents
dictionaries
Series statement
Springer Series in Statistics,
http://library.link/vocab/subjectName
• Mathematical statistics
• Statistics
• Econometrics
• Statistical Theory and Methods
• Statistics for Business, Management, Economics, Finance, Insurance
• Statistics for Social Sciences, Humanities, Law
• Econometrics
Label
Partial Identification of Probability Distributions, by Charles F. Manski, (electronic resource)
Instantiates
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
• cr
Content category
text
Content type code
• txt
Contents
Introduction: Partial Identification and Credible Inference -- Missing Outcomes -- Instrumental Variables -- Conditional Prediction with Missing Data -- Contaminated Outcomes -- Regressions, Short and Long -- Response-Based Sampling -- Analysis of Treatment Response -- Mnotone Treatment Response -- Monotone Instrumental Variables -- The Mixing Problem
Dimensions
unknown
Edition
1st ed. 2003.
Extent
1 online resource (187 p.)
Form of item
online
Isbn
9780387217864
Media category
computer
Media type code
• c
Other control number
10.1007/b97478
Specific material designation
remote
System control number
• (CKB)1000000000227415
• (EBL)3036224
• (SSID)ssj0000218214
• (PQKBManifestationID)11181112
• (PQKBTitleCode)TC0000218214
• (PQKBWorkID)10214397
• (PQKB)11587014
• (DE-He213)978-0-387-21786-4
• (MiAaPQ)EBC3036224
• (EXLCZ)991000000000227415
Label
Partial Identification of Probability Distributions, by Charles F. Manski, (electronic resource)
Publication
Note
Description based upon print version of record
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
• cr
Content category
text
Content type code
• txt
Contents
Introduction: Partial Identification and Credible Inference -- Missing Outcomes -- Instrumental Variables -- Conditional Prediction with Missing Data -- Contaminated Outcomes -- Regressions, Short and Long -- Response-Based Sampling -- Analysis of Treatment Response -- Mnotone Treatment Response -- Monotone Instrumental Variables -- The Mixing Problem
Dimensions
unknown
Edition
1st ed. 2003.
Extent
1 online resource (187 p.)
Form of item
online
Isbn
9780387217864
Media category
computer
Media type code
• c
Other control number
10.1007/b97478
Specific material designation
remote
System control number
• (CKB)1000000000227415
• (EBL)3036224
• (SSID)ssj0000218214
• (PQKBManifestationID)11181112
• (PQKBTitleCode)TC0000218214
• (PQKBWorkID)10214397
• (PQKB)11587014
• (DE-He213)978-0-387-21786-4
• (MiAaPQ)EBC3036224
• (EXLCZ)991000000000227415

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