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The Resource Biased sampling, over-identified parameter problems and beyond, Jing Qin

Biased sampling, over-identified parameter problems and beyond, Jing Qin

Label
Biased sampling, over-identified parameter problems and beyond
Title
Biased sampling, over-identified parameter problems and beyond
Statement of responsibility
Jing Qin
Creator
Author
Subject
Language
eng
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Qin, Jing
Dewey number
519.5/2
Index
no index present
LC call number
QA276.6
Literary form
non fiction
Nature of contents
dictionaries
Series statement
ICSA book series in statistics
http://library.link/vocab/subjectName
Sampling (Statistics)
Label
Biased sampling, over-identified parameter problems and beyond, Jing Qin
Instantiates
Publication
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; Acknowledgements; Contents; 1 Examples and Basic Theories for Length Biased Sampling Problems; 1.1 Length Biased Sampling Examples; 1.2 Basic Properties of Length Biased Sampling Problems; 1.3 Stochastic Ordering; 1.4 Lorenz Curve; 1.5 Characterization of Length Biased Distribution; 2 Brief Introduction of Renewal Process; 2.1 Basic Concepts; 2.2 Forward and Backward Recurrence Times; 2.3 Basic Results on Poisson Process; 3 Heuristical Introduction of General Biased Sampling with Various Applications ; 3.1 Natural Selection Biased Sampling Problems
  • 3.2 Modelling Based Selection Biased Sampling Problems4 Brief Review of Parametric Likelihood Inferences; 4.1 Kullback -- Leibler Information and Entropy Concepts; 4.2 Issues in Maximum Likelihood Estimation; 4.3 Popular Inference Methods in the Presence of Nuisance Parameters; 4.4 Quasi-likelihood Methods in Linear Regression Models; 4.5 Composite Likelihoods and Corrected Likelihoods; 4.6 Variable Selection and Akaike Criterion; 4.7 Two Useful Maximization Algorithms; 4.8 Likelihood Based Inference with Inequality Constraints; 5 Optimal Estimating Function Theory
  • 5.1 Godambe's Optimality Criterion5.2 Applications of Godambe's Theory in Missing Covariate Problems; 5.3 Godambe's Theory in Length Biased Sampling AFT Models; 5.4 Ancillarity and Fisher Information with Nuisance Parameters; 5.5 Projection Methods in Parametric Models; 5.6 Reduce Sensitivity with Respect to Nuisance Parameters; 6 Projection Methods in General Semiparametric Models; 6.1 Projection Method for the Mean Estimation and Linear Regression Model; 6.2 Information Contained in the Conditional Expectation Model; 6.3 Projection Method in a Two Sample Density Ratio Model
  • 6.4 Information Calculation in Over-identified Semiparametric Models6.5 Information Calculation for Missing Data Problems; 6.6 A Non-root n Consistent Estimator Example; 7 Generalized Method of Moments; 7.1 Basic Concepts on Generalized Method of Moments; 7.2 An Optimal Result Based on an Embed Exponential Family; 7.3 Applications of GMM; 8 Empirical Likelihood with Applications; 8.1 Definition of Empirical Likelihood and Basic Properties; 8.2 General Theory of Empirical Likelihood in Estimating Equations; 8.3 Miscellaneous Topics on Empirical Likelihood
  • 8.4 Hybrid Likelihoods and Utilization Auxiliary Information8.5 Combine Summarized Information: A More Flexible Method in Meta Analysis; 9 Kullback -- Leibler Likelihood and Entropy Family ; 9.1 Minimize Kullback -- Leibler Divergence Subject to Moment Constraints; 9.2 Entropy Family in the Presence of Covariates; 9.3 Some Miscellaneous Results; 9.4 Entropy Family with Fixed Margins in Discrete Case; 9.5 Generalized Empirical Likelihoods; 9.6 Inference for Exponential Family with Specified Mean Function; 10 General Theory on Biased Sampling Problems
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9789811048562
Media category
computer
Media MARC source
rdamedia
Media type code
c
Reformatting quality
preservation
Sound
unknown sound
Specific material designation
remote
System control number
ocn990267807
Label
Biased sampling, over-identified parameter problems and beyond, Jing Qin
Publication
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; Acknowledgements; Contents; 1 Examples and Basic Theories for Length Biased Sampling Problems; 1.1 Length Biased Sampling Examples; 1.2 Basic Properties of Length Biased Sampling Problems; 1.3 Stochastic Ordering; 1.4 Lorenz Curve; 1.5 Characterization of Length Biased Distribution; 2 Brief Introduction of Renewal Process; 2.1 Basic Concepts; 2.2 Forward and Backward Recurrence Times; 2.3 Basic Results on Poisson Process; 3 Heuristical Introduction of General Biased Sampling with Various Applications ; 3.1 Natural Selection Biased Sampling Problems
  • 3.2 Modelling Based Selection Biased Sampling Problems4 Brief Review of Parametric Likelihood Inferences; 4.1 Kullback -- Leibler Information and Entropy Concepts; 4.2 Issues in Maximum Likelihood Estimation; 4.3 Popular Inference Methods in the Presence of Nuisance Parameters; 4.4 Quasi-likelihood Methods in Linear Regression Models; 4.5 Composite Likelihoods and Corrected Likelihoods; 4.6 Variable Selection and Akaike Criterion; 4.7 Two Useful Maximization Algorithms; 4.8 Likelihood Based Inference with Inequality Constraints; 5 Optimal Estimating Function Theory
  • 5.1 Godambe's Optimality Criterion5.2 Applications of Godambe's Theory in Missing Covariate Problems; 5.3 Godambe's Theory in Length Biased Sampling AFT Models; 5.4 Ancillarity and Fisher Information with Nuisance Parameters; 5.5 Projection Methods in Parametric Models; 5.6 Reduce Sensitivity with Respect to Nuisance Parameters; 6 Projection Methods in General Semiparametric Models; 6.1 Projection Method for the Mean Estimation and Linear Regression Model; 6.2 Information Contained in the Conditional Expectation Model; 6.3 Projection Method in a Two Sample Density Ratio Model
  • 6.4 Information Calculation in Over-identified Semiparametric Models6.5 Information Calculation for Missing Data Problems; 6.6 A Non-root n Consistent Estimator Example; 7 Generalized Method of Moments; 7.1 Basic Concepts on Generalized Method of Moments; 7.2 An Optimal Result Based on an Embed Exponential Family; 7.3 Applications of GMM; 8 Empirical Likelihood with Applications; 8.1 Definition of Empirical Likelihood and Basic Properties; 8.2 General Theory of Empirical Likelihood in Estimating Equations; 8.3 Miscellaneous Topics on Empirical Likelihood
  • 8.4 Hybrid Likelihoods and Utilization Auxiliary Information8.5 Combine Summarized Information: A More Flexible Method in Meta Analysis; 9 Kullback -- Leibler Likelihood and Entropy Family ; 9.1 Minimize Kullback -- Leibler Divergence Subject to Moment Constraints; 9.2 Entropy Family in the Presence of Covariates; 9.3 Some Miscellaneous Results; 9.4 Entropy Family with Fixed Margins in Discrete Case; 9.5 Generalized Empirical Likelihoods; 9.6 Inference for Exponential Family with Specified Mean Function; 10 General Theory on Biased Sampling Problems
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9789811048562
Media category
computer
Media MARC source
rdamedia
Media type code
c
Reformatting quality
preservation
Sound
unknown sound
Specific material designation
remote
System control number
ocn990267807

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