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Developing econometrics [[electronic resource] /] / Hengqing Tong, T. Krishna Kumar, Yangxin Huang
Developing econometrics [[electronic resource] /] / Hengqing Tong, T. Krishna Kumar, Yangxin Huang
Autore Tong Hengping <1971->
Pubbl/distr/stampa Hoboken, : Wiley, 2011
Descrizione fisica 1 online resource (487 p.)
Disciplina 330.01/5195
Altri autori (Persone) KumarT. Krishna
HuangYang Xin
Soggetto topico Econometrics
Econometric models
Data mining
ISBN 1-119-96090-8
1-283-30680-8
9786613306807
1-119-95423-1
1-119-95424-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Developing Econometrics; Contents; Foreword; Preface; Acknowledgements; 1 Introduction; 1.1 Nature and Scope of Econometrics; 1.1.1 What is Econometrics and Why Study Econometrics?; 1.1.2 Econometrics and Scientific Credibility of Business and Economic Decisions; 1.2 Types of Economic Problems, Types of Data, and Types of Models; 1.2.1 Experimental Data from a Marketing Experiment; 1.2.2 Cross-Section Data: National Sample Survey Data on Consumer Expenditure; 1.2.3 Non-Experimental Data Taken from Secondary Sources: The Case of Pharmaceutical Industry in India
1.2.4 Loan Default Risk of a Customer and the Problem Facing Decision on a Loan Application1.2.5 Panel Data: Performance of Banks in India by the Type of Ownership after Economic Reforms; 1.2.6 Single Time Series Data: The Bombay Stock Exchange (BSE) Index; 1.2.7 Multiple Time Series Data: Stock Prices in BRIC Countries; 1.3 Pattern Recognition and Exploratory Data Analysis; 1.3.1 Some Basic Issues in Econometric Modeling; 1.3.2 Exploratory Data Analysis Using Correlations and Scatter Diagrams: The Relative Importance of Managerial Function and Labor
1.3.3 Cleaning and Reprocessing Data to Discover Patterns: BSE Index Data1.4 Econometric Modeling: The Roadmap of This Book; 1.4.1 The Econometric Modeling Strategy; 1.4.2 Plan of the Book; Electronic References for Chapter 1; References; 2 Independent Variables in Linear Regression Models; 2.1 Brief Review of Linear Regression; 2.1.1 Brief Review of Univariate Linear Regression; 2.1.2 Brief Review of Multivariate Linear Regression; 2.2 Selection of Independent Variable and Stepwise Regression; 2.2.1 Principles of Selection of Independent Variables; 2.2.2 Stepwise Regression
2.3 Multivariate Data Transformation and Polynomial Regression2.3.1 Linear Regression after Multivariate Data Transformation; 2.3.2 Polynomial Regression on an Independent Variable; 2.3.3 Multivariable Polynomial Regression; 2.4 Column Multicollinearity in Design Matrix and Ridge Regression; 2.4.1 Effect of Column Multicollinearity of Design Matrix; 2.4.2 Ridge Regression; 2.4.3 Ridge Trace Analysis and Ridge Parameter Selection; 2.4.4 Generalized Ridge Regression; 2.5 Recombination of Independent Variable and Principal Components Regression; 2.5.1 Concept of Principal Components Regression
2.5.2 Determination of Principal ComponentElectronic References for Chapter 2; References; 3 Alternative Structures of Residual Error in Linear Regression Models; 3.1 Heteroscedasticity: Consequences and Tests for Its Existence; 3.1.1 Consequences of Heteroscedasticity; 3.1.2 Tests for Heteroscedasticity; 3.2 Generalized Linear Model with Covariance Being a Diagonal Matrix; 3.2.1 Diagonal Covariance Matrix and Weighted Least Squares; 3.2.2 Model with Two Unknown Variances; 3.2.3 Multiplicative Heteroscedastic Model; 3.3 Autocorrelation in a Linear Model
3.3.1 Linear Model with First-Order Residual Autoregression
Record Nr. UNINA-9910139568403321
Tong Hengping <1971->  
Hoboken, : Wiley, 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Developing econometrics / / Hengqing Tong, T. Krishna Kumar, Yangxin Huang
Developing econometrics / / Hengqing Tong, T. Krishna Kumar, Yangxin Huang
Autore Tong Hengping <1971->
Edizione [2nd ed.]
Pubbl/distr/stampa Hoboken, : Wiley, 2011
Descrizione fisica 1 online resource (487 p.)
Disciplina 330.01/5195
Altri autori (Persone) KumarT. Krishna
HuangYang Xin
Soggetto topico Econometrics
Econometric models
Data mining
ISBN 9786613306807
9781119960904
1119960908
9781283306805
1283306808
9781119954231
1119954231
9781119954248
111995424X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Developing Econometrics; Contents; Foreword; Preface; Acknowledgements; 1 Introduction; 1.1 Nature and Scope of Econometrics; 1.1.1 What is Econometrics and Why Study Econometrics?; 1.1.2 Econometrics and Scientific Credibility of Business and Economic Decisions; 1.2 Types of Economic Problems, Types of Data, and Types of Models; 1.2.1 Experimental Data from a Marketing Experiment; 1.2.2 Cross-Section Data: National Sample Survey Data on Consumer Expenditure; 1.2.3 Non-Experimental Data Taken from Secondary Sources: The Case of Pharmaceutical Industry in India
1.2.4 Loan Default Risk of a Customer and the Problem Facing Decision on a Loan Application1.2.5 Panel Data: Performance of Banks in India by the Type of Ownership after Economic Reforms; 1.2.6 Single Time Series Data: The Bombay Stock Exchange (BSE) Index; 1.2.7 Multiple Time Series Data: Stock Prices in BRIC Countries; 1.3 Pattern Recognition and Exploratory Data Analysis; 1.3.1 Some Basic Issues in Econometric Modeling; 1.3.2 Exploratory Data Analysis Using Correlations and Scatter Diagrams: The Relative Importance of Managerial Function and Labor
1.3.3 Cleaning and Reprocessing Data to Discover Patterns: BSE Index Data1.4 Econometric Modeling: The Roadmap of This Book; 1.4.1 The Econometric Modeling Strategy; 1.4.2 Plan of the Book; Electronic References for Chapter 1; References; 2 Independent Variables in Linear Regression Models; 2.1 Brief Review of Linear Regression; 2.1.1 Brief Review of Univariate Linear Regression; 2.1.2 Brief Review of Multivariate Linear Regression; 2.2 Selection of Independent Variable and Stepwise Regression; 2.2.1 Principles of Selection of Independent Variables; 2.2.2 Stepwise Regression
2.3 Multivariate Data Transformation and Polynomial Regression2.3.1 Linear Regression after Multivariate Data Transformation; 2.3.2 Polynomial Regression on an Independent Variable; 2.3.3 Multivariable Polynomial Regression; 2.4 Column Multicollinearity in Design Matrix and Ridge Regression; 2.4.1 Effect of Column Multicollinearity of Design Matrix; 2.4.2 Ridge Regression; 2.4.3 Ridge Trace Analysis and Ridge Parameter Selection; 2.4.4 Generalized Ridge Regression; 2.5 Recombination of Independent Variable and Principal Components Regression; 2.5.1 Concept of Principal Components Regression
2.5.2 Determination of Principal ComponentElectronic References for Chapter 2; References; 3 Alternative Structures of Residual Error in Linear Regression Models; 3.1 Heteroscedasticity: Consequences and Tests for Its Existence; 3.1.1 Consequences of Heteroscedasticity; 3.1.2 Tests for Heteroscedasticity; 3.2 Generalized Linear Model with Covariance Being a Diagonal Matrix; 3.2.1 Diagonal Covariance Matrix and Weighted Least Squares; 3.2.2 Model with Two Unknown Variances; 3.2.3 Multiplicative Heteroscedastic Model; 3.3 Autocorrelation in a Linear Model
3.3.1 Linear Model with First-Order Residual Autoregression
Record Nr. UNINA-9910810589003321
Tong Hengping <1971->  
Hoboken, : Wiley, 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui