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Biblioteca

MARC Lista (tabellare)
Applied Time Series Analysis for the Social Sciences : Specification, Estimation, and Inference
Applied Time Series Analysis for the Social Sciences : Specification, Estimation, and Inference
Autore Baker Regina M
Edizione [1st ed.]
Pubbl/distr/stampa Newark : , : John Wiley & Sons, Incorporated, , 2025
Descrizione fisica 1 online resource (242 pages)
Disciplina 519.5/5
Collana Wiley Series in Probability and Statistics Series
Soggetto topico Time-series analysis
Social sciences - Statistical methods
ISBN 1-119-01047-0
1-119-01049-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Foundations -- Properties of time series : mean and variance stationarity -- Properties of time series : autocorrelation, the autocorrelation function and the partial autocorrelation function -- Examining time series properties : univariate ARIMA estimation and forecasting -- ARIMA intervention models -- ARIMA with non-binary explanatory variables -- OLS and the Gauss-Markov assumptions -- Autoregressive distributed lag models -- Cointegration and error correction -- General-to-specific modeling and the LSE school approach -- Vector autoregression : fundamental concepts -- Vector autoregression : details.
Record Nr. UNINA-9911046558503321
Baker Regina M  
Newark : , : John Wiley & Sons, Incorporated, , 2025
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Constrained statistical inference : inequality, order, and shape restrictions / Mervyn J. Silvapulle, Pranab K. Sen
Constrained statistical inference : inequality, order, and shape restrictions / Mervyn J. Silvapulle, Pranab K. Sen
Autore Silvapulle, Mervyn J., 1951-
Pubbl/distr/stampa Hoboken, N.J. : Wiley-Interscience, c2005
Descrizione fisica xvii, 532 p. : ill. ; 24 cm
Disciplina 519.5/5
Altri autori (Persone) Sen, Pranab Kumar, 1937-
Collana Wiley series in probability and statistics
Soggetto topico Multivariate analysis
ISBN 0471208272
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991002584999707536
Silvapulle, Mervyn J., 1951-  
Hoboken, N.J. : Wiley-Interscience, c2005
Materiale a stampa
Lo trovi qui: Univ. del Salento
Opac: Controlla la disponibilità qui
A course in time series analysis [[electronic resource] /] / edited by Daniel Peña, George C. Tiao, Ruey S. Tsay
A course in time series analysis [[electronic resource] /] / edited by Daniel Peña, George C. Tiao, Ruey S. Tsay
Pubbl/distr/stampa New York, : J. Wiley, c2001
Descrizione fisica 1 online resource (494 p.)
Disciplina 519.5/5
519.55
Altri autori (Persone) PeñaDaniel <1948->
TiaoGeorge C. <1933->
TsayRuey S. <1951->
Collana Wiley series in probability and statistics
Soggetto topico Time-series analysis
ISBN 1-282-24252-0
9786613813640
1-118-03297-7
1-118-03122-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto pt. 1. Basic concepts in univariate time series -- pt. 2. Advanced topics in univariate time series -- pt. 3. Multivariate time series.
Record Nr. UNISA-996213510403316
New York, : J. Wiley, c2001
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
A course in time series analysis / / edited by Daniel Pena, George C. Tiao, Ruey S. Tsay
A course in time series analysis / / edited by Daniel Pena, George C. Tiao, Ruey S. Tsay
Pubbl/distr/stampa New York, : J. Wiley, c2001
Descrizione fisica 1 online resource (494 p.)
Disciplina 519.5/5
Altri autori (Persone) PeñaDaniel <1948->
TiaoGeorge C. <1933->
TsayRuey S. <1951->
Collana Wiley series in probability and statistics
Soggetto topico Time-series analysis
ISBN 9786613813640
9781282242524
1282242520
9781118032978
1118032977
9781118031223
1118031229
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto pt. 1. Basic concepts in univariate time series -- pt. 2. Advanced topics in univariate time series -- pt. 3. Multivariate time series.
Record Nr. UNINA-9910139189303321
New York, : J. Wiley, c2001
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Efficient algorithms of time series processing and their applications [[electronic resource] /] / G. Sh. Tsitsiashvili, editor
Efficient algorithms of time series processing and their applications [[electronic resource] /] / G. Sh. Tsitsiashvili, editor
Pubbl/distr/stampa New York, : Nova Science Publishers, c2009
Descrizione fisica 1 online resource (109 p.)
Disciplina 519.5/5
Altri autori (Persone) T͡Sit͡siashviliG. Sh (Gurami Shalvovich)
Soggetto topico Time-series analysis
Algorithms
Soggetto genere / forma Electronic books.
ISBN 1-61728-387-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910460017403321
New York, : Nova Science Publishers, c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Efficient algorithms of time series processing and their applications [[electronic resource] /] / G. Sh. Tsitsiashvili, editor
Efficient algorithms of time series processing and their applications [[electronic resource] /] / G. Sh. Tsitsiashvili, editor
Pubbl/distr/stampa New York, : Nova Science Publishers, c2009
Descrizione fisica 1 online resource (109 p.)
Disciplina 519.5/5
Altri autori (Persone) T͡Sit͡siashviliG. Sh (Gurami Shalvovich)
Soggetto topico Time-series analysis
Algorithms
ISBN 1-61728-387-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910785182503321
New York, : Nova Science Publishers, c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Efficient algorithms of time series processing and their applications / / G. Sh. Tsitsiashvili, editor
Efficient algorithms of time series processing and their applications / / G. Sh. Tsitsiashvili, editor
Edizione [1st ed.]
Pubbl/distr/stampa New York, : Nova Science Publishers, c2009
Descrizione fisica 1 online resource (109 p.)
Disciplina 519.5/5
Altri autori (Persone) T︠S︡it︠s︡iashviliG. Sh (Gurami Shalvovich)
Soggetto topico Time-series analysis
Algorithms
ISBN 1-61728-387-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- EFFICIENT ALGORITHMS OF TIME SERIES PROCESSING AND THEIR APPLICATIONS -- EFFICIENT ALGORITHMS OF TIME SERIES PROCESSING AND THEIR APPLICATIONS -- CONTENTS -- PREFACE -- Chapter 1.INTRA-ANNUAL BUNDLES OF CLIMATIC PARAMETERS -- ABSTRACT -- INTRODUCTION -- 1. DATA -- 2. METHODS INVESTIGATION -- 3. DISCUSSION OF RESULTS -- CONCLUSION -- REFERENCES -- Chapter 2. APPLICATION OF EXPERIENCE METHOD OF THE RECOGNITION BY INTERVAL FOR MAKING PROGNOSIS ON THE TATAR STRAIT(JAPAN SEA) ICE-COVER EXTREMITY -- ABSTRACT -- INTRODUCTION -- 1. DATA AND METHODS OF EXPLORATION -- 2. PECULIARITIES OF THE ATMOSPHERIC PROCESSES THAT PROVIDE FORMATION OF ANOMALOUS ICE COVER IN THE TATAR STRAIT -- 3. RESULTS OF CALCULATIONS -- CONCLUSION -- REFERENCES -- Chapter 3. FACTOR TEMPORAL PROGNOSIS OF CRITICAL LEVELS OF HUMAN INFECTION RATE -- REFERENCES -- Chapter 4SPACE-TIME PROGNOSIS OF TICK-BORNE ENCEPHALITIS FOCI FUNCTIONING -- REFERENCES -- Chapter 5. SYSTEM APPROACH IN DEMOGRAPHIC INVESTIGATIONS -- ABSTRACT -- MORTALITY IN PRIMORSKIY KRAY DEPENDING ON AGE -- REFERENCES -- Chapter 6. THE DETERMINATION OF FIXITY FACTORS IN DYNAMIC RISE OF CITIES -- ABSTRACT -- REFERENCES -- Chapter 7. EXPLORATION OF VARIABILITY IN THE ABOVE-EARTH AIR TEMPERATURE OVER THE FAR EAST REGIONS BY THE METHOD OF RESIDUAL VARIABILITY OF TEMPORAL ROW -- ABSTRACT -- 1. DATA AND METHOD OF EXPLORATION -- 2. PRINCIPAL RESULTS OF RESEARCH -- CONCLUSION -- REFERENCES -- Chapter 8. ESTIMATES OF VARIANCES IN TIME SERIES STATISTICS -- 1. MODIFIED EMPIRICAL VARIANCE -- 2. VARIATION OF DEVIATION FROM POLYNOMIAL REGRESSION FUNCTION -- 3. MODIFIED EMPIRICAL COVARIANCE -- REFERENCES -- INDEX -- Blank Page.
Record Nr. UNINA-9910953942603321
New York, : Nova Science Publishers, c2009
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Forecasting with dynamic regression models [[electronic resource] /] / Alan Pankratz
Forecasting with dynamic regression models [[electronic resource] /] / Alan Pankratz
Autore Pankratz Alan <1944->
Pubbl/distr/stampa New York, : John Wiley & Sons, 1991
Descrizione fisica 1 online resource (410 p.)
Disciplina 519.5/5
519.55
Collana Wiley series in probability and mathematical statistics. Applied probability and statistics
Soggetto topico Time-series analysis
Regression analysis
Prediction theory
Soggetto genere / forma Electronic books.
ISBN 1-283-44612-X
9786613446121
1-118-15052-X
1-118-15078-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Forecasting with Dynamic Regression Models; Contents; Preface; Chapter 1 Introduction and Overview; 1.1 Related Time Series; 1.2 Overview: Dynamic Regression Models; 1.3 Box and Jenkins' Modeling Strategy; 1.4 Correlation; 1.5 Layout of the Book; Questions and Problems; Chapter 2 A Primer on ARIMA Models; 2.1 Introduction; 2.2 Stationary Variance and Mean; 2.3 Autocorrelation; 2.4 Five Stationary ARIMA Processes; 2.5 ARIMA Modeling in Practice; 2.6 Backshift Notation; 2.7 Seasonal Models; 2.8 Combined Nonseasonal and Seasonal Processes; 2.9 Forecasting; 2.10 Extended Autocorrelation Function
2.11 Interpreting ARIMA Model ForecastsQuestions and Problems; Case 1 Federal Government Receipts (ARIMA); Chapter 3 A Primer on Regression Models; 3.1 Two Types of Data; 3.2 The Population Regression Function (PRF) with One Input; 3.3 The Sample Regression Function (SRF) with One Input; 3.4 Properties of the Least-Squares Estimators; 3.5 Goodness of Fit (R2); 3.6 Statistical Inference; 3.7 Multiple Regression; 3.8 Selected Issues in Regression; 3.9 Application to Time Series Data; Questions and Problems; Case 2 Federal Government Receipts (Dynamic Regression); Case 3 Kilowatt-Hours Used
Chapter 4 Rational Distributed Lag Models4.1 Linear Distributed Lag Transfer Functions; 4.2 A Special Case: The Koyck Model; 4.3 Rational Distributed Lags; 4.4 The Complete Rational Form DR Model and Some Special Cases 163; Questions and Problems; Chapter 5 Building Dynamic Regression Models: Model Identification; 5.1 Overview; 5.2 Preliminary Modeling Steps; 5.3 The Linear Transfer Function (LTF) Identification Method; 5.4 Rules for Identifying Rational Distributed Lag Transfer Functions; Questions and Problems; Appendix 5A The Corner Table
Appendix 5B Transfer Function Identification Using Prewhitening and Cross CorrelationsChapter 6 Building Dynamic Regression Models: Model Checking, Reformulation and Evaluation; 6.1 Diagnostic Checking and Model Reformulation; 6.2 Evaluating Estimation Stage Results; Questions and Problems; Case 4 Housing Starts and Sales; Case 5 Industrial Production, Stock Prices, and Vendor Performance; Chapter 7 Intervention Analysis; 7.1 Introduction; 7.2 Pulse Interventions; 7.3 Step Interventions; 7.4 Building Intervention Models; 7.5 Multiple and Compound Interventions; Questions and Problems
Case 6 Year-End LoadingChapter 8 Intervention and Outlier Detection and Treatment; 8.1 The Rationale for Intervention and Outlier Detection; 8.2 Models for Intervention and Outlier Detection; 8.3 Likelihood Ratio Criteria; 8.4 An Iterative Detection Procedure; 8.5 Application; 8.6 Detected Events Near the End of a Series; Questions and Problems; Appendix 8A BASIC Program to Detect AO, LS, and IO Events; Appendix 8B Specifying IO Events in the SCA System; Chapter 9 Estimation and Forecasting; 9.1 DR Model Estimation; 9.2 Forecasting; Questions and Problems
Appendix 9A A BASIC Routine for Computing the Nonbiasing Factor in (9.2.24)
Record Nr. UNINA-9910139721303321
Pankratz Alan <1944->  
New York, : John Wiley & Sons, 1991
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Forecasting with dynamic regression models [[electronic resource] /] / Alan Pankratz
Forecasting with dynamic regression models [[electronic resource] /] / Alan Pankratz
Autore Pankratz Alan <1944->
Pubbl/distr/stampa New York, : John Wiley & Sons, 1991
Descrizione fisica 1 online resource (410 p.)
Disciplina 519.5/5
519.55
Collana Wiley series in probability and mathematical statistics. Applied probability and statistics
Soggetto topico Time-series analysis
Regression analysis
Prediction theory
ISBN 1-283-44612-X
9786613446121
1-118-15052-X
1-118-15078-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Forecasting with Dynamic Regression Models; Contents; Preface; Chapter 1 Introduction and Overview; 1.1 Related Time Series; 1.2 Overview: Dynamic Regression Models; 1.3 Box and Jenkins' Modeling Strategy; 1.4 Correlation; 1.5 Layout of the Book; Questions and Problems; Chapter 2 A Primer on ARIMA Models; 2.1 Introduction; 2.2 Stationary Variance and Mean; 2.3 Autocorrelation; 2.4 Five Stationary ARIMA Processes; 2.5 ARIMA Modeling in Practice; 2.6 Backshift Notation; 2.7 Seasonal Models; 2.8 Combined Nonseasonal and Seasonal Processes; 2.9 Forecasting; 2.10 Extended Autocorrelation Function
2.11 Interpreting ARIMA Model ForecastsQuestions and Problems; Case 1 Federal Government Receipts (ARIMA); Chapter 3 A Primer on Regression Models; 3.1 Two Types of Data; 3.2 The Population Regression Function (PRF) with One Input; 3.3 The Sample Regression Function (SRF) with One Input; 3.4 Properties of the Least-Squares Estimators; 3.5 Goodness of Fit (R2); 3.6 Statistical Inference; 3.7 Multiple Regression; 3.8 Selected Issues in Regression; 3.9 Application to Time Series Data; Questions and Problems; Case 2 Federal Government Receipts (Dynamic Regression); Case 3 Kilowatt-Hours Used
Chapter 4 Rational Distributed Lag Models4.1 Linear Distributed Lag Transfer Functions; 4.2 A Special Case: The Koyck Model; 4.3 Rational Distributed Lags; 4.4 The Complete Rational Form DR Model and Some Special Cases 163; Questions and Problems; Chapter 5 Building Dynamic Regression Models: Model Identification; 5.1 Overview; 5.2 Preliminary Modeling Steps; 5.3 The Linear Transfer Function (LTF) Identification Method; 5.4 Rules for Identifying Rational Distributed Lag Transfer Functions; Questions and Problems; Appendix 5A The Corner Table
Appendix 5B Transfer Function Identification Using Prewhitening and Cross CorrelationsChapter 6 Building Dynamic Regression Models: Model Checking, Reformulation and Evaluation; 6.1 Diagnostic Checking and Model Reformulation; 6.2 Evaluating Estimation Stage Results; Questions and Problems; Case 4 Housing Starts and Sales; Case 5 Industrial Production, Stock Prices, and Vendor Performance; Chapter 7 Intervention Analysis; 7.1 Introduction; 7.2 Pulse Interventions; 7.3 Step Interventions; 7.4 Building Intervention Models; 7.5 Multiple and Compound Interventions; Questions and Problems
Case 6 Year-End LoadingChapter 8 Intervention and Outlier Detection and Treatment; 8.1 The Rationale for Intervention and Outlier Detection; 8.2 Models for Intervention and Outlier Detection; 8.3 Likelihood Ratio Criteria; 8.4 An Iterative Detection Procedure; 8.5 Application; 8.6 Detected Events Near the End of a Series; Questions and Problems; Appendix 8A BASIC Program to Detect AO, LS, and IO Events; Appendix 8B Specifying IO Events in the SCA System; Chapter 9 Estimation and Forecasting; 9.1 DR Model Estimation; 9.2 Forecasting; Questions and Problems
Appendix 9A A BASIC Routine for Computing the Nonbiasing Factor in (9.2.24)
Record Nr. UNINA-9910829964503321
Pankratz Alan <1944->  
New York, : John Wiley & Sons, 1991
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Forecasting with dynamic regression models / / Alan Pankratz
Forecasting with dynamic regression models / / Alan Pankratz
Autore Pankratz Alan <1944->
Pubbl/distr/stampa New York, : John Wiley & Sons, 1991
Descrizione fisica 1 online resource (410 p.)
Disciplina 519.5/5
Collana Wiley series in probability and mathematical statistics. Applied probability and statistics
Soggetto topico Time-series analysis
Regression analysis
Prediction theory
ISBN 9786613446121
9781283446129
128344612X
9781118150528
111815052X
9781118150788
1118150783
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Forecasting with Dynamic Regression Models; Contents; Preface; Chapter 1 Introduction and Overview; 1.1 Related Time Series; 1.2 Overview: Dynamic Regression Models; 1.3 Box and Jenkins' Modeling Strategy; 1.4 Correlation; 1.5 Layout of the Book; Questions and Problems; Chapter 2 A Primer on ARIMA Models; 2.1 Introduction; 2.2 Stationary Variance and Mean; 2.3 Autocorrelation; 2.4 Five Stationary ARIMA Processes; 2.5 ARIMA Modeling in Practice; 2.6 Backshift Notation; 2.7 Seasonal Models; 2.8 Combined Nonseasonal and Seasonal Processes; 2.9 Forecasting; 2.10 Extended Autocorrelation Function
2.11 Interpreting ARIMA Model ForecastsQuestions and Problems; Case 1 Federal Government Receipts (ARIMA); Chapter 3 A Primer on Regression Models; 3.1 Two Types of Data; 3.2 The Population Regression Function (PRF) with One Input; 3.3 The Sample Regression Function (SRF) with One Input; 3.4 Properties of the Least-Squares Estimators; 3.5 Goodness of Fit (R2); 3.6 Statistical Inference; 3.7 Multiple Regression; 3.8 Selected Issues in Regression; 3.9 Application to Time Series Data; Questions and Problems; Case 2 Federal Government Receipts (Dynamic Regression); Case 3 Kilowatt-Hours Used
Chapter 4 Rational Distributed Lag Models4.1 Linear Distributed Lag Transfer Functions; 4.2 A Special Case: The Koyck Model; 4.3 Rational Distributed Lags; 4.4 The Complete Rational Form DR Model and Some Special Cases 163; Questions and Problems; Chapter 5 Building Dynamic Regression Models: Model Identification; 5.1 Overview; 5.2 Preliminary Modeling Steps; 5.3 The Linear Transfer Function (LTF) Identification Method; 5.4 Rules for Identifying Rational Distributed Lag Transfer Functions; Questions and Problems; Appendix 5A The Corner Table
Appendix 5B Transfer Function Identification Using Prewhitening and Cross CorrelationsChapter 6 Building Dynamic Regression Models: Model Checking, Reformulation and Evaluation; 6.1 Diagnostic Checking and Model Reformulation; 6.2 Evaluating Estimation Stage Results; Questions and Problems; Case 4 Housing Starts and Sales; Case 5 Industrial Production, Stock Prices, and Vendor Performance; Chapter 7 Intervention Analysis; 7.1 Introduction; 7.2 Pulse Interventions; 7.3 Step Interventions; 7.4 Building Intervention Models; 7.5 Multiple and Compound Interventions; Questions and Problems
Case 6 Year-End LoadingChapter 8 Intervention and Outlier Detection and Treatment; 8.1 The Rationale for Intervention and Outlier Detection; 8.2 Models for Intervention and Outlier Detection; 8.3 Likelihood Ratio Criteria; 8.4 An Iterative Detection Procedure; 8.5 Application; 8.6 Detected Events Near the End of a Series; Questions and Problems; Appendix 8A BASIC Program to Detect AO, LS, and IO Events; Appendix 8B Specifying IO Events in the SCA System; Chapter 9 Estimation and Forecasting; 9.1 DR Model Estimation; 9.2 Forecasting; Questions and Problems
Appendix 9A A BASIC Routine for Computing the Nonbiasing Factor in (9.2.24)
Record Nr. UNINA-9911018815303321
Pankratz Alan <1944->  
New York, : John Wiley & Sons, 1991
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui