top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Handbook of computational econometrics [[electronic resource] /] / edited by David A. Belsley, Erricos Kontoghiorghes
Handbook of computational econometrics [[electronic resource] /] / edited by David A. Belsley, Erricos Kontoghiorghes
Pubbl/distr/stampa Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : Wiley, c2009
Descrizione fisica 1 online resource (516 p.)
Disciplina 330.015195
330.0285/555
330.0285555
Altri autori (Persone) BelsleyDavid A
KontoghiorghesErricos John
Collana Wiley Series in Computational Statistics
Soggetto topico Econometrics - Computer programs
Economics - Statistical methods
Econometrics - Data processing
Soggetto genere / forma Electronic books.
ISBN 1-282-27912-2
9786612279126
0-470-74891-5
0-470-74890-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Handbook of Computational Econometrics; Contents; List of Contributors; Preface; 1 Econometric software; 1.1 Introduction; 1.2 The nature of econometric software; 1.2.1 The characteristics of early econometric software; 1.2.2 The expansive development of econometric software; 1.2.3 Econometric computing and the microcomputer; 1.3 The existing characteristics of econometric software; 1.3.1 Software characteristics: broadening and deepening; 1.3.2 Software characteristics: interface development; 1.3.3 Directives versus constructive commands; 1.3.4 Econometric software design implications
1.4 ConclusionAcknowledgments; References; 2 The accuracy of econometric software; 2.1 Introduction; 2.2 Inaccurate econometric results; 2.2.1 Inaccurate simulation results; 2.2.2 Inaccurate GARCH results; 2.2.3 Inaccurate VAR results; 2.3 Entry-level tests; 2.4 Intermediate-level tests; 2.4.1 NIST Statistical Reference Datasets; 2.4.2 Statistical distributions; 2.4.3 Random numbers; 2.5 Conclusions; Acknowledgments; References; 3 Heuristic optimization methods in econometrics; 3.1 Traditional numerical versus heuristic optimization methods; 3.1.1 Optimization in econometrics
3.1.2 Optimization heuristics3.1.3 An incomplete collection of applications of optimization heuristics in econometrics; 3.1.4 Structure and instructions for use of the chapter; 3.2 Heuristic optimization; 3.2.1 Basic concepts; 3.2.2 Trajectory methods; 3.2.3 Population-based methods; 3.2.4 Hybrid metaheuristics; 3.3 Stochastics of the solution; 3.3.1 Optimization as stochastic mapping; 3.3.2 Convergence of heuristics; 3.3.3 Convergence of optimization-based estimators; 3.4 General guidelines for the use of optimization heuristics; 3.4.1 Implementation; 3.4.2 Presentation of results
3.5 Selected applications3.5.1 Model selection in VAR models; 3.5.2 High breakdown point estimation; 3.6 Conclusions; Acknowledgments; References; 4 Algorithms for minimax and expected value optimization; 4.1 Introduction; 4.2 An interior point algorithm; 4.2.1 Subgradient of (x) and basic iteration; 4.2.2 Primal-dual step size selection; 4.2.3 Choice of c and μ; 4.3 Global optimization of polynomial minimax problems; 4.3.1 The algorithm; 4.4 Expected value optimization; 4.4.1 An algorithm for expected value optimization
4.5 Evaluation framework for minimax robust policies and expected value optimizationAcknowledgments; References; 5 Nonparametric estimation; 5.1 Introduction; 5.1.1 Comments on software; 5.2 Density estimation; 5.2.1 Some illustrations; 5.3 Nonparametric regression; 5.3.1 An illustration; 5.3.2 Multiple predictors; 5.3.3 Some illustrations; 5.3.4 Estimating conditional associations; 5.3.5 An illustration; 5.4 Nonparametric inferential techniques; 5.4.1 Some motivating examples; 5.4.2 A bootstrap-t method; 5.4.3 The percentile bootstrap method; 5.4.4 Simple ordinary least squares regression
5.4.5 Regression with multiple predictors
Record Nr. UNINA-9910139925403321
Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : Wiley, c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook of computational econometrics [[electronic resource] /] / edited by David A. Belsley, Erricos Kontoghiorghes
Handbook of computational econometrics [[electronic resource] /] / edited by David A. Belsley, Erricos Kontoghiorghes
Pubbl/distr/stampa Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : Wiley, c2009
Descrizione fisica 1 online resource (516 p.)
Disciplina 330.015195
330.0285/555
330.0285555
Altri autori (Persone) BelsleyDavid A
KontoghiorghesErricos John
Collana Wiley Series in Computational Statistics
Soggetto topico Econometrics - Computer programs
Economics - Statistical methods
Econometrics - Data processing
ISBN 1-282-27912-2
9786612279126
0-470-74891-5
0-470-74890-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Handbook of Computational Econometrics; Contents; List of Contributors; Preface; 1 Econometric software; 1.1 Introduction; 1.2 The nature of econometric software; 1.2.1 The characteristics of early econometric software; 1.2.2 The expansive development of econometric software; 1.2.3 Econometric computing and the microcomputer; 1.3 The existing characteristics of econometric software; 1.3.1 Software characteristics: broadening and deepening; 1.3.2 Software characteristics: interface development; 1.3.3 Directives versus constructive commands; 1.3.4 Econometric software design implications
1.4 ConclusionAcknowledgments; References; 2 The accuracy of econometric software; 2.1 Introduction; 2.2 Inaccurate econometric results; 2.2.1 Inaccurate simulation results; 2.2.2 Inaccurate GARCH results; 2.2.3 Inaccurate VAR results; 2.3 Entry-level tests; 2.4 Intermediate-level tests; 2.4.1 NIST Statistical Reference Datasets; 2.4.2 Statistical distributions; 2.4.3 Random numbers; 2.5 Conclusions; Acknowledgments; References; 3 Heuristic optimization methods in econometrics; 3.1 Traditional numerical versus heuristic optimization methods; 3.1.1 Optimization in econometrics
3.1.2 Optimization heuristics3.1.3 An incomplete collection of applications of optimization heuristics in econometrics; 3.1.4 Structure and instructions for use of the chapter; 3.2 Heuristic optimization; 3.2.1 Basic concepts; 3.2.2 Trajectory methods; 3.2.3 Population-based methods; 3.2.4 Hybrid metaheuristics; 3.3 Stochastics of the solution; 3.3.1 Optimization as stochastic mapping; 3.3.2 Convergence of heuristics; 3.3.3 Convergence of optimization-based estimators; 3.4 General guidelines for the use of optimization heuristics; 3.4.1 Implementation; 3.4.2 Presentation of results
3.5 Selected applications3.5.1 Model selection in VAR models; 3.5.2 High breakdown point estimation; 3.6 Conclusions; Acknowledgments; References; 4 Algorithms for minimax and expected value optimization; 4.1 Introduction; 4.2 An interior point algorithm; 4.2.1 Subgradient of (x) and basic iteration; 4.2.2 Primal-dual step size selection; 4.2.3 Choice of c and μ; 4.3 Global optimization of polynomial minimax problems; 4.3.1 The algorithm; 4.4 Expected value optimization; 4.4.1 An algorithm for expected value optimization
4.5 Evaluation framework for minimax robust policies and expected value optimizationAcknowledgments; References; 5 Nonparametric estimation; 5.1 Introduction; 5.1.1 Comments on software; 5.2 Density estimation; 5.2.1 Some illustrations; 5.3 Nonparametric regression; 5.3.1 An illustration; 5.3.2 Multiple predictors; 5.3.3 Some illustrations; 5.3.4 Estimating conditional associations; 5.3.5 An illustration; 5.4 Nonparametric inferential techniques; 5.4.1 Some motivating examples; 5.4.2 A bootstrap-t method; 5.4.3 The percentile bootstrap method; 5.4.4 Simple ordinary least squares regression
5.4.5 Regression with multiple predictors
Record Nr. UNINA-9910830811703321
Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : Wiley, c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Handbook of computational econometrics / / edited by David A. Belsley, Erricos Kontoghiorghes
Handbook of computational econometrics / / edited by David A. Belsley, Erricos Kontoghiorghes
Pubbl/distr/stampa Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : Wiley, c2009
Descrizione fisica 1 online resource (516 p.)
Disciplina 330.015195
330.0285/555
330.0285555
Altri autori (Persone) BelsleyDavid A
KontoghiorghesErricos John
Collana Wiley Series in Computational Statistics
Soggetto topico Econometrics - Computer programs
Economics - Statistical methods
Econometrics - Data processing
ISBN 9786612279126
9781282279124
1282279122
9780470748916
0470748915
9780470748909
0470748907
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Handbook of Computational Econometrics; Contents; List of Contributors; Preface; 1 Econometric software; 1.1 Introduction; 1.2 The nature of econometric software; 1.2.1 The characteristics of early econometric software; 1.2.2 The expansive development of econometric software; 1.2.3 Econometric computing and the microcomputer; 1.3 The existing characteristics of econometric software; 1.3.1 Software characteristics: broadening and deepening; 1.3.2 Software characteristics: interface development; 1.3.3 Directives versus constructive commands; 1.3.4 Econometric software design implications
1.4 ConclusionAcknowledgments; References; 2 The accuracy of econometric software; 2.1 Introduction; 2.2 Inaccurate econometric results; 2.2.1 Inaccurate simulation results; 2.2.2 Inaccurate GARCH results; 2.2.3 Inaccurate VAR results; 2.3 Entry-level tests; 2.4 Intermediate-level tests; 2.4.1 NIST Statistical Reference Datasets; 2.4.2 Statistical distributions; 2.4.3 Random numbers; 2.5 Conclusions; Acknowledgments; References; 3 Heuristic optimization methods in econometrics; 3.1 Traditional numerical versus heuristic optimization methods; 3.1.1 Optimization in econometrics
3.1.2 Optimization heuristics3.1.3 An incomplete collection of applications of optimization heuristics in econometrics; 3.1.4 Structure and instructions for use of the chapter; 3.2 Heuristic optimization; 3.2.1 Basic concepts; 3.2.2 Trajectory methods; 3.2.3 Population-based methods; 3.2.4 Hybrid metaheuristics; 3.3 Stochastics of the solution; 3.3.1 Optimization as stochastic mapping; 3.3.2 Convergence of heuristics; 3.3.3 Convergence of optimization-based estimators; 3.4 General guidelines for the use of optimization heuristics; 3.4.1 Implementation; 3.4.2 Presentation of results
3.5 Selected applications3.5.1 Model selection in VAR models; 3.5.2 High breakdown point estimation; 3.6 Conclusions; Acknowledgments; References; 4 Algorithms for minimax and expected value optimization; 4.1 Introduction; 4.2 An interior point algorithm; 4.2.1 Subgradient of (x) and basic iteration; 4.2.2 Primal-dual step size selection; 4.2.3 Choice of c and μ; 4.3 Global optimization of polynomial minimax problems; 4.3.1 The algorithm; 4.4 Expected value optimization; 4.4.1 An algorithm for expected value optimization
4.5 Evaluation framework for minimax robust policies and expected value optimizationAcknowledgments; References; 5 Nonparametric estimation; 5.1 Introduction; 5.1.1 Comments on software; 5.2 Density estimation; 5.2.1 Some illustrations; 5.3 Nonparametric regression; 5.3.1 An illustration; 5.3.2 Multiple predictors; 5.3.3 Some illustrations; 5.3.4 Estimating conditional associations; 5.3.5 An illustration; 5.4 Nonparametric inferential techniques; 5.4.1 Some motivating examples; 5.4.2 A bootstrap-t method; 5.4.3 The percentile bootstrap method; 5.4.4 Simple ordinary least squares regression
5.4.5 Regression with multiple predictors
Record Nr. UNINA-9911020105503321
Chichester, West Sussex, U.K. ; ; Hoboken, N.J., : Wiley, c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui