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The Resource Applying Generalized Linear Models, by James K. Lindsey, (electronic resource)
Applying Generalized Linear Models, by James K. Lindsey, (electronic resource)
Resource Information
The item Applying Generalized Linear Models, by James K. Lindsey, (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.
Resource Information
The item Applying Generalized Linear Models, by James K. Lindsey, (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.
 Summary
 Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas  linear normal, categorical, and survival models  have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liège, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books
 Language

 eng
 eng
 Edition
 1st ed. 1997.
 Extent
 1 online resource (271 p.)
 Note
 Description based upon print version of record
 Contents

 Generalized Linear Modelling: Statistical Modelling
 Exponential Dispersion Models
 Linear Structure
 Three Components of a GLM
 Possible Models
 Inference
 Exercises. Discrete Data: Log Linear Models
 Models of Change
 Overdispersion
 Exercises. Fitting and Comparing Probability Distributions: Fitting Distributions
 Setting Up the Model
 Special Cases
 Exercises. Growth Curves: Exponential Growth Curves
 Logistic Growth Curve
 Gomperz Growth Curve
 More Complex Models
 Exercises. Time Series: Poisson Processes
 Markov Processes
 Repeated Measurements
 Exercises. Survival Data: General Concepts
 'Nonparametric' Estimation
 Parametric Models
 'Semiparametric' Models
 Exercises. Event Histories: Event Histories and Survival Distributions
 Counting processes
 Modelling Event Histories
 Generalizations
 Exercises. Spatial data: Spatial Interaction
 Spatial Patterns
 Exercises. Normal Models: Linear Regression
 Analysis of Variance
 Nonlinear Regression
 Exercises. Dynamic Models: Dynamic Generalized Linear Models
 Normal Models
 Count Data
 Positive Response Data
 Continuous Time Nonlinear Models. Appendices: Inference
 Diagnostics
 References
 Index
 Isbn
 9780387227306
 Label
 Applying Generalized Linear Models
 Title
 Applying Generalized Linear Models
 Statement of responsibility
 by James K. Lindsey
 Language

 eng
 eng
 Summary
 Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas  linear normal, categorical, and survival models  have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liège, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books
 http://library.link/vocab/creatorName
 Lindsey, James K
 Dewey number
 519.5/3
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
 18ZHgEazh_0
 Language note
 English
 LC call number

 QA273.A1274.9
 QA274274.9
 Literary form
 non fiction
 Nature of contents
 dictionaries
 Series statement
 Springer Texts in Statistics,
 http://library.link/vocab/subjectName

 Distribution (Probability theory
 Mathematical statistics
 Statistics
 Probability Theory and Stochastic Processes
 Statistical Theory and Methods
 Statistics for Life Sciences, Medicine, Health Sciences
 Label
 Applying Generalized Linear Models, by James K. Lindsey, (electronic resource)
 Note
 Description based upon print version of record
 Bibliography note
 Includes bibliographical references (p. [231]242) abd index
 Carrier category
 online resource
 Carrier category code
 cr
 Content category
 text
 Content type code
 txt
 Contents
 Generalized Linear Modelling: Statistical Modelling  Exponential Dispersion Models  Linear Structure  Three Components of a GLM  Possible Models  Inference  Exercises. Discrete Data: Log Linear Models  Models of Change  Overdispersion  Exercises. Fitting and Comparing Probability Distributions: Fitting Distributions  Setting Up the Model  Special Cases  Exercises. Growth Curves: Exponential Growth Curves  Logistic Growth Curve  Gomperz Growth Curve  More Complex Models  Exercises. Time Series: Poisson Processes  Markov Processes  Repeated Measurements  Exercises. Survival Data: General Concepts  'Nonparametric' Estimation  Parametric Models  'Semiparametric' Models  Exercises. Event Histories: Event Histories and Survival Distributions  Counting processes  Modelling Event Histories  Generalizations  Exercises. Spatial data: Spatial Interaction  Spatial Patterns  Exercises. Normal Models: Linear Regression  Analysis of Variance  Nonlinear Regression  Exercises. Dynamic Models: Dynamic Generalized Linear Models  Normal Models  Count Data  Positive Response Data  Continuous Time Nonlinear Models. Appendices: Inference  Diagnostics  References  Index
 Dimensions
 unknown
 Edition
 1st ed. 1997.
 Extent
 1 online resource (271 p.)
 Form of item
 online
 Isbn
 9780387227306
 Media category
 computer
 Media type code
 c
 Other control number
 10.1007/b98856
 Specific material designation
 remote
 System control number

 (CKB)111087027062476
 (EBL)3035258
 (SSID)ssj0000104838
 (PQKBManifestationID)11127862
 (PQKBTitleCode)TC0000104838
 (PQKBWorkID)10100507
 (PQKB)10785693
 (DEHe213)9780387227306
 (MiAaPQ)EBC3035258
 (EXLCZ)99111087027062476
 Label
 Applying Generalized Linear Models, by James K. Lindsey, (electronic resource)
 Note
 Description based upon print version of record
 Bibliography note
 Includes bibliographical references (p. [231]242) abd index
 Carrier category
 online resource
 Carrier category code
 cr
 Content category
 text
 Content type code
 txt
 Contents
 Generalized Linear Modelling: Statistical Modelling  Exponential Dispersion Models  Linear Structure  Three Components of a GLM  Possible Models  Inference  Exercises. Discrete Data: Log Linear Models  Models of Change  Overdispersion  Exercises. Fitting and Comparing Probability Distributions: Fitting Distributions  Setting Up the Model  Special Cases  Exercises. Growth Curves: Exponential Growth Curves  Logistic Growth Curve  Gomperz Growth Curve  More Complex Models  Exercises. Time Series: Poisson Processes  Markov Processes  Repeated Measurements  Exercises. Survival Data: General Concepts  'Nonparametric' Estimation  Parametric Models  'Semiparametric' Models  Exercises. Event Histories: Event Histories and Survival Distributions  Counting processes  Modelling Event Histories  Generalizations  Exercises. Spatial data: Spatial Interaction  Spatial Patterns  Exercises. Normal Models: Linear Regression  Analysis of Variance  Nonlinear Regression  Exercises. Dynamic Models: Dynamic Generalized Linear Models  Normal Models  Count Data  Positive Response Data  Continuous Time Nonlinear Models. Appendices: Inference  Diagnostics  References  Index
 Dimensions
 unknown
 Edition
 1st ed. 1997.
 Extent
 1 online resource (271 p.)
 Form of item
 online
 Isbn
 9780387227306
 Media category
 computer
 Media type code
 c
 Other control number
 10.1007/b98856
 Specific material designation
 remote
 System control number

 (CKB)111087027062476
 (EBL)3035258
 (SSID)ssj0000104838
 (PQKBManifestationID)11127862
 (PQKBTitleCode)TC0000104838
 (PQKBWorkID)10100507
 (PQKB)10785693
 (DEHe213)9780387227306
 (MiAaPQ)EBC3035258
 (EXLCZ)99111087027062476
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Architecture LibraryBorrow itGould Hall 830 Van Vleet Oval Rm. 105, Norman, OK, 73019, US35.205706 97.445050



Chinese Literature Translation ArchiveBorrow it401 W. Brooks St., RM 414, Norman, OK, 73019, US35.207487 97.447906

Engineering LibraryBorrow itFelgar Hall 865 Asp Avenue, Rm. 222, Norman, OK, 73019, US35.205706 97.445050

Fine Arts LibraryBorrow itCatlett Music Center 500 West Boyd Street, Rm. 20, Norman, OK, 73019, US35.210371 97.448244

Harry W. Bass Business History CollectionBorrow it401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US35.207487 97.447906

History of Science CollectionsBorrow it401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US35.207487 97.447906

John and Mary Nichols Rare Books and Special CollectionsBorrow it401 W. Brooks St., Rm. 509NW, Norman, OK, 73019, US35.207487 97.447906


Price College Digital LibraryBorrow itAdams Hall 102 307 West Brooks St., Norman, OK, 73019, US35.210371 97.448244

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