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Advanced Kalman filtering, least-squares and modeling [[electronic resource] ] : a practical handbook / / Bruce P. Gibbs
Advanced Kalman filtering, least-squares and modeling [[electronic resource] ] : a practical handbook / / Bruce P. Gibbs
Autore Gibbs Bruce. P. <1946->
Pubbl/distr/stampa Hoboken, NJ, : Wiley Pub., c2011
Descrizione fisica 1 online resource (627 p.)
Disciplina 620.0042
620.0072/7
Soggetto topico Kalman filtering
Least squares
Soggetto genere / forma Electronic books.
ISBN 1-283-02519-1
9786613025197
0-470-89004-5
0-470-89003-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ADVANCED KALMAN FILTERING, LEAST-SQUARES AND MODELING; CONTENTS; PREFACE; CHAPTER 1: INTRODUCTION; CHAPTER 2: SYSTEM DYNAMICS AND MODELS; CHAPTER 3: MODELING EXAMPLES; CHAPTER 4: LINEAR LEAST - SQUARES ESTIMATION: FUNDAMENTALS; CHAPTER 5: LINEAR LEAST - SQUARES ESTIMATION: SOLUTION TECHNIQUES; CHAPTER 6: LEAST - SQUARES ESTIMATION: MODEL ERRORS AND MODEL ORDER; 6.1 ASSESSING THE VALIDITY OF THE SOLUTION; 6.2 SOLUTION ERROR ANALYSIS; 6.3 REGRESSION ANALYSIS FOR WEIGHTED LEAST SQUARES; 6.4 SUMMARY; CHAPTER 7: LEAST - SQUARES ESTIMATION: CONSTRAINTS, NONLINEAR MODELS, AND ROBUST TECHNIQUES
CHAPTER 8: KALMAN FILTERINGCHAPTER 9: FILTERING FOR NONLINEAR SYSTEMS, SMOOTHING, ERROR ANALYSIS/MODEL DESIGN, AND MEASUREMENT PREPROCESSING; CHAPTER 10: FACTORED (SQUARE - ROOT) FILTERING; CHAPTER 11: ADVANCED FILTERING TOPICS; CHAPTER 12: EMPIRICAL MODELING; APPENDIX A: SUMMARY OF VECTOR/MATRIX OPERATIONS; APPENDIX B: PROBABILITY AND RANDOM VARIABLES; BIBLIOGRAPHY; INDEX
Record Nr. UNINA-9910140851003321
Gibbs Bruce. P. <1946->  
Hoboken, NJ, : Wiley Pub., c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Advanced Kalman filtering, least-squares and modeling : a practical handbook / / Bruce P. Gibbs
Advanced Kalman filtering, least-squares and modeling : a practical handbook / / Bruce P. Gibbs
Autore Gibbs Bruce. P. <1946->
Pubbl/distr/stampa Hoboken, NJ, : Wiley Pub., c2011
Descrizione fisica 1 online resource (627 p.)
Disciplina 620.0042
620.0072/7
Soggetto topico Kalman filtering
Least squares
ISBN 1-283-02519-1
9786613025197
0-470-89004-5
0-470-89003-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto ADVANCED KALMAN FILTERING, LEAST-SQUARES AND MODELING; CONTENTS; PREFACE; CHAPTER 1: INTRODUCTION; CHAPTER 2: SYSTEM DYNAMICS AND MODELS; CHAPTER 3: MODELING EXAMPLES; CHAPTER 4: LINEAR LEAST - SQUARES ESTIMATION: FUNDAMENTALS; CHAPTER 5: LINEAR LEAST - SQUARES ESTIMATION: SOLUTION TECHNIQUES; CHAPTER 6: LEAST - SQUARES ESTIMATION: MODEL ERRORS AND MODEL ORDER; 6.1 ASSESSING THE VALIDITY OF THE SOLUTION; 6.2 SOLUTION ERROR ANALYSIS; 6.3 REGRESSION ANALYSIS FOR WEIGHTED LEAST SQUARES; 6.4 SUMMARY; CHAPTER 7: LEAST - SQUARES ESTIMATION: CONSTRAINTS, NONLINEAR MODELS, AND ROBUST TECHNIQUES
CHAPTER 8: KALMAN FILTERINGCHAPTER 9: FILTERING FOR NONLINEAR SYSTEMS, SMOOTHING, ERROR ANALYSIS/MODEL DESIGN, AND MEASUREMENT PREPROCESSING; CHAPTER 10: FACTORED (SQUARE - ROOT) FILTERING; CHAPTER 11: ADVANCED FILTERING TOPICS; CHAPTER 12: EMPIRICAL MODELING; APPENDIX A: SUMMARY OF VECTOR/MATRIX OPERATIONS; APPENDIX B: PROBABILITY AND RANDOM VARIABLES; BIBLIOGRAPHY; INDEX
Record Nr. UNINA-9910877349703321
Gibbs Bruce. P. <1946->  
Hoboken, NJ, : Wiley Pub., c2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Advances in nonlinear parameter optimization / Rudiger Schmidt
Advances in nonlinear parameter optimization / Rudiger Schmidt
Autore Schmidt, Rudiger
Pubbl/distr/stampa Berlin : Springer-Verlag, 1982
Descrizione fisica vi, 159 p. : ill. ; 24 cm.
Disciplina 519
Collana Lecture notes in control and information sciences ; 37
Soggetto topico Least squares
Mathematical optimization
Mathematical programming
Nonlinear theories
ISBN 3540113967
Classificazione AMS 49J27
AMS 65H10
AMS 65K05
AMS 65K10
AMS 90C31
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991000647909707536
Schmidt, Rudiger  
Berlin : Springer-Verlag, 1982
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Analytic approximations for application to spacecraft optical navigation on short data arcs / / by Alton P. Mayo and William M. Adams, Jr
Analytic approximations for application to spacecraft optical navigation on short data arcs / / by Alton P. Mayo and William M. Adams, Jr
Autore Mayo Alton P.
Pubbl/distr/stampa Washington, D.C. : , : National Aeronautics and Space Administration, , November 1968
Descrizione fisica 1 online resource (30 pages) : illustrations
Collana NASA technical note
Soggetto topico Space vehicles - Orbit
Space vehicles - Speed
Navigation (Astronautics) - Measurement
Space vehicles - Tracking
Least squares
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910714077003321
Mayo Alton P.  
Washington, D.C. : , : National Aeronautics and Space Administration, , November 1968
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida [[electronic resource] /] / by Dann K. Yobbi ; prepared in cooperation with Tampa Bay Water and the Southwest Florida Water Management District
Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida [[electronic resource] /] / by Dann K. Yobbi ; prepared in cooperation with Tampa Bay Water and the Southwest Florida Water Management District
Autore Yobbi D. K
Pubbl/distr/stampa Tallahassee, Fla. : , : U.S. Dept. of the Interior, U.S. Geological Survey
Collana Water-resources investigations report
Soggetto topico Groundwater flow - Florida - Mathematical models
Water-supply - Florida
Least squares
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Application of nonlinear least squares regression to ground-water flow modeling, west-central Florida
Record Nr. UNINA-9910692156903321
Yobbi D. K  
Tallahassee, Fla. : , : U.S. Dept. of the Interior, U.S. Geological Survey
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Application of nonlinear-regression methods to a ground-water flow model of the Albuquerque Basin, New Mexico / / by Claire R. Tiedeman, John Michael Kernodle, and Douglas P. McAda
Application of nonlinear-regression methods to a ground-water flow model of the Albuquerque Basin, New Mexico / / by Claire R. Tiedeman, John Michael Kernodle, and Douglas P. McAda
Autore Tiedeman Claire R.
Pubbl/distr/stampa Menlo Park, California : , : U.S. Geological Survey, , 1998
Descrizione fisica 1 online resource (vi, 90 pages) : illustrations, maps
Collana Water-resources investigations report
Soggetto topico Groundwater flow - New Mexico - Albuquerque Basin - Mathematical models
Water table - New Mexico - Albuquerque Basin - Mathematical models
Regression analysis
Groundwater flow - Mathematical models
Least squares
Water table - Mathematical models
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Ground-water flow model of the Albuquerque Basin, New Mexico
Record Nr. UNINA-9910716889903321
Tiedeman Claire R.  
Menlo Park, California : , : U.S. Geological Survey, , 1998
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Data reduction and error analysis for the physical sciences / P. Bevington
Data reduction and error analysis for the physical sciences / P. Bevington
Autore Bevington, P.
Pubbl/distr/stampa New York : McGraw-Hill Book Co., 1969
Descrizione fisica xv, 336 p. : ill. ; 22 cm.
Soggetto topico Data reduction
Error analysis
Least squares
Classificazione 53.0.42
519'.6
QA278
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991000882469707536
Bevington, P.  
New York : McGraw-Hill Book Co., 1969
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Generalized least squares [[electronic resource] /] / Takeaki Kariya, Hiroshi Kurata
Generalized least squares [[electronic resource] /] / Takeaki Kariya, Hiroshi Kurata
Autore Kariya Takeaki
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2004
Descrizione fisica 1 online resource (313 p.)
Disciplina 511
511.42
511/.42
Altri autori (Persone) KurataHiroshi <1967->
Collana Wiley series in probability and statistics
Soggetto topico Least squares
Soggetto genere / forma Electronic books.
ISBN 1-280-27206-6
9786610272068
0-470-29876-6
0-470-86698-5
0-470-86699-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Contents; Preface; 1 Preliminaries; 1.1 Overview; 1.2 Multivariate Normal and Wishart Distributions; 1.3 Elliptically Symmetric Distributions; 1.4 Group Invariance; 1.5 Problems; 2 Generalized Least Squares Estimators; 2.1 Overview; 2.2 General Linear Regression Model; 2.3 Generalized Least Squares Estimators; 2.4 Finiteness of Moments and Typical GLSEs; 2.5 Empirical Example: CO[sub(2)] Emission Data; 2.6 Empirical Example: Bond Price Data; 2.7 Problems; 3 Nonlinear Versions of the Gauss-Markov Theorem; 3.1 Overview; 3.2 Generalized Least Squares Predictors
3.3 A Nonlinear Version of the Gauss-Markov Theorem in Prediction3.4 A Nonlinear Version of the Gauss-Markov Theorem in Estimation; 3.5 An Application to GLSEs with Iterated Residuals; 3.6 Problems; 4 SUR and Heteroscedastic Models; 4.1 Overview; 4.2 GLSEs with a Simple Covariance Structure; 4.3 Upper Bound for the Covariance Matrix of a GLSE; 4.4 Upper Bound Problem for the UZE in an SUR Model; 4.5 Upper Bound Problems for a GLSE in a Heteroscedastic Model; 4.6 Empirical Example: CO[sub(2)] Emission Data; 4.7 Problems; 5 Serial Correlation Model; 5.1 Overview
5.2 Upper Bound for the Risk Matrix of a GLSE5.3 Upper Bound Problem for a GLSE in the Anderson Model; 5.4 Upper Bound Problem for a GLSE in a Two-equation Heteroscedastic Model; 5.5 Empirical Example: Automobile Data; 5.6 Problems; 6 Normal Approximation; 6.1 Overview; 6.2 Uniform Bounds for Normal Approximations to the Probability Density Functions; 6.3 Uniform Bounds for Normal Approximations to the Cumulative Distribution Functions; 6.4 Problems; 7 Extension of Gauss-Markov Theorem; 7.1 Overview; 7.2 An Equivalence Relation on S(n); 7.3 A Maximal Extension of the Gauss-Markov Theorem
7.4 Nonlinear Versions of the Gauss-Markov Theorem7.5 Problems; 8 Some Further Extensions; 8.1 Overview; 8.2 Concentration Inequalities for the Gauss-Markov Estimator; 8.3 Efficiency of GLSEs under Elliptical Symmetry; 8.4 Degeneracy of the Distributions of GLSEs; 8.5 Problems; 9 Growth Curve Model and GLSEs; 9.1 Overview; 9.2 Condition for the Identical Equality between the GME and the OLSE; 9.3 GLSEs and Nonlinear Version of the Gauss-Markov Theorem; 9.4 Analysis Based on a Canonical Form; 9.5 Efficiency of GLSEs; 9.6 Problems; A: Appendix
A.1 Asymptotic Equivalence of the Estimators of θ in the AR(1) Error Model and Anderson ModelBibliography; Index; A; B; C; D; E; G; H; I; K; L; M; N; O; R; S; U; W
Record Nr. UNINA-9910145905103321
Kariya Takeaki  
Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Generalized least squares [[electronic resource] /] / Takeaki Kariya, Hiroshi Kurata
Generalized least squares [[electronic resource] /] / Takeaki Kariya, Hiroshi Kurata
Autore Kariya Takeaki
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2004
Descrizione fisica 1 online resource (313 p.)
Disciplina 511
511.42
511/.42
Altri autori (Persone) KurataHiroshi <1967->
Collana Wiley series in probability and statistics
Soggetto topico Least squares
ISBN 1-280-27206-6
9786610272068
0-470-29876-6
0-470-86698-5
0-470-86699-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Contents; Preface; 1 Preliminaries; 1.1 Overview; 1.2 Multivariate Normal and Wishart Distributions; 1.3 Elliptically Symmetric Distributions; 1.4 Group Invariance; 1.5 Problems; 2 Generalized Least Squares Estimators; 2.1 Overview; 2.2 General Linear Regression Model; 2.3 Generalized Least Squares Estimators; 2.4 Finiteness of Moments and Typical GLSEs; 2.5 Empirical Example: CO[sub(2)] Emission Data; 2.6 Empirical Example: Bond Price Data; 2.7 Problems; 3 Nonlinear Versions of the Gauss-Markov Theorem; 3.1 Overview; 3.2 Generalized Least Squares Predictors
3.3 A Nonlinear Version of the Gauss-Markov Theorem in Prediction3.4 A Nonlinear Version of the Gauss-Markov Theorem in Estimation; 3.5 An Application to GLSEs with Iterated Residuals; 3.6 Problems; 4 SUR and Heteroscedastic Models; 4.1 Overview; 4.2 GLSEs with a Simple Covariance Structure; 4.3 Upper Bound for the Covariance Matrix of a GLSE; 4.4 Upper Bound Problem for the UZE in an SUR Model; 4.5 Upper Bound Problems for a GLSE in a Heteroscedastic Model; 4.6 Empirical Example: CO[sub(2)] Emission Data; 4.7 Problems; 5 Serial Correlation Model; 5.1 Overview
5.2 Upper Bound for the Risk Matrix of a GLSE5.3 Upper Bound Problem for a GLSE in the Anderson Model; 5.4 Upper Bound Problem for a GLSE in a Two-equation Heteroscedastic Model; 5.5 Empirical Example: Automobile Data; 5.6 Problems; 6 Normal Approximation; 6.1 Overview; 6.2 Uniform Bounds for Normal Approximations to the Probability Density Functions; 6.3 Uniform Bounds for Normal Approximations to the Cumulative Distribution Functions; 6.4 Problems; 7 Extension of Gauss-Markov Theorem; 7.1 Overview; 7.2 An Equivalence Relation on S(n); 7.3 A Maximal Extension of the Gauss-Markov Theorem
7.4 Nonlinear Versions of the Gauss-Markov Theorem7.5 Problems; 8 Some Further Extensions; 8.1 Overview; 8.2 Concentration Inequalities for the Gauss-Markov Estimator; 8.3 Efficiency of GLSEs under Elliptical Symmetry; 8.4 Degeneracy of the Distributions of GLSEs; 8.5 Problems; 9 Growth Curve Model and GLSEs; 9.1 Overview; 9.2 Condition for the Identical Equality between the GME and the OLSE; 9.3 GLSEs and Nonlinear Version of the Gauss-Markov Theorem; 9.4 Analysis Based on a Canonical Form; 9.5 Efficiency of GLSEs; 9.6 Problems; A: Appendix
A.1 Asymptotic Equivalence of the Estimators of θ in the AR(1) Error Model and Anderson ModelBibliography; Index; A; B; C; D; E; G; H; I; K; L; M; N; O; R; S; U; W
Record Nr. UNINA-9910830436903321
Kariya Takeaki  
Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Generalized least squares / / Takeaki Kariya, Hiroshi Kurata
Generalized least squares / / Takeaki Kariya, Hiroshi Kurata
Autore Kariya Takeaki
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2004
Descrizione fisica 1 online resource (313 p.)
Disciplina 511/.42
Altri autori (Persone) KurataHiroshi <1967->
Collana Wiley series in probability and statistics
Soggetto topico Least squares
ISBN 1-280-27206-6
9786610272068
0-470-29876-6
0-470-86698-5
0-470-86699-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Contents; Preface; 1 Preliminaries; 1.1 Overview; 1.2 Multivariate Normal and Wishart Distributions; 1.3 Elliptically Symmetric Distributions; 1.4 Group Invariance; 1.5 Problems; 2 Generalized Least Squares Estimators; 2.1 Overview; 2.2 General Linear Regression Model; 2.3 Generalized Least Squares Estimators; 2.4 Finiteness of Moments and Typical GLSEs; 2.5 Empirical Example: CO[sub(2)] Emission Data; 2.6 Empirical Example: Bond Price Data; 2.7 Problems; 3 Nonlinear Versions of the Gauss-Markov Theorem; 3.1 Overview; 3.2 Generalized Least Squares Predictors
3.3 A Nonlinear Version of the Gauss-Markov Theorem in Prediction3.4 A Nonlinear Version of the Gauss-Markov Theorem in Estimation; 3.5 An Application to GLSEs with Iterated Residuals; 3.6 Problems; 4 SUR and Heteroscedastic Models; 4.1 Overview; 4.2 GLSEs with a Simple Covariance Structure; 4.3 Upper Bound for the Covariance Matrix of a GLSE; 4.4 Upper Bound Problem for the UZE in an SUR Model; 4.5 Upper Bound Problems for a GLSE in a Heteroscedastic Model; 4.6 Empirical Example: CO[sub(2)] Emission Data; 4.7 Problems; 5 Serial Correlation Model; 5.1 Overview
5.2 Upper Bound for the Risk Matrix of a GLSE5.3 Upper Bound Problem for a GLSE in the Anderson Model; 5.4 Upper Bound Problem for a GLSE in a Two-equation Heteroscedastic Model; 5.5 Empirical Example: Automobile Data; 5.6 Problems; 6 Normal Approximation; 6.1 Overview; 6.2 Uniform Bounds for Normal Approximations to the Probability Density Functions; 6.3 Uniform Bounds for Normal Approximations to the Cumulative Distribution Functions; 6.4 Problems; 7 Extension of Gauss-Markov Theorem; 7.1 Overview; 7.2 An Equivalence Relation on S(n); 7.3 A Maximal Extension of the Gauss-Markov Theorem
7.4 Nonlinear Versions of the Gauss-Markov Theorem7.5 Problems; 8 Some Further Extensions; 8.1 Overview; 8.2 Concentration Inequalities for the Gauss-Markov Estimator; 8.3 Efficiency of GLSEs under Elliptical Symmetry; 8.4 Degeneracy of the Distributions of GLSEs; 8.5 Problems; 9 Growth Curve Model and GLSEs; 9.1 Overview; 9.2 Condition for the Identical Equality between the GME and the OLSE; 9.3 GLSEs and Nonlinear Version of the Gauss-Markov Theorem; 9.4 Analysis Based on a Canonical Form; 9.5 Efficiency of GLSEs; 9.6 Problems; A: Appendix
A.1 Asymptotic Equivalence of the Estimators of θ in the AR(1) Error Model and Anderson ModelBibliography; Index; A; B; C; D; E; G; H; I; K; L; M; N; O; R; S; U; W
Record Nr. UNINA-9910877013603321
Kariya Takeaki  
Chichester, West Sussex, England ; ; Hoboken, NJ, : Wiley, c2004
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui