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[null,"1.","Record Nr.",null,"UNINA9910460599503321"]
[null,null,"Autore",null,"Kennedy Liam"]
[null,null,"Titolo",null,"Unhappy the Land [[electronic resource] ] : The Most Oppressed People Ever, the Irish?"]
[null,null,"Pubbl/distr/stampa",null,"Dublin 4, : Merrion, 2015"]
[null,null,"ISBN",null,"1-78537-030-8"]
[null,null,"Descrizione fisica",null,"1 online resource (305 p.)"]
[null,null,"Disciplina",null,"941.5"]
[null,null,"Soggetti",null,"Irish - History"]
[{"$nulls":4},"Ireland"]
[{"$nulls":4},"Regions & Countries - Europe"]
[{"$nulls":4},"History & Archaeology"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,"Nota di contenuto",null,"Cover; Front Matter; Title Page; Contents; Preface and Acknowledgements; List of Tables; Introduction; PART 1; The Long View; Chapter One; A Most Opressed People?; Chapter Two; The Planter and the Gael; Chapter Three; Nationalism and Unionism in Ireland; PART 2; Famine in Ireland; Chapter Four; Cry Holocaust: The Great Irish Famine and the Jewish Holocaust; Chapter Five; Ireland, Irish-America and the Man who 'Invented' Genocide; Part 3; The Revolutionary Decade; Chapter Six; Harbinger of Reaction: The Great Ulster Covenant; Chapter Seven; Bad Blood: the Proclamation of the Irish Republic"]
[{"$nulls":4},"Chapter EightTexting Terror: 1912 and 1916; Chapter Nine; Was There an Irish War of Independence?; Endnotes; Bibliography; Index"]
[null,"2.","Record Nr.",null,"UNINA9910827811503321"]
[null,null,"Autore",null,"Montgomery Douglas C."]
[null,null,"Titolo",null,"Introduction to time series analysis and forecasting / / Douglas C. Montgomery, Cheryl L. Jennings, Murat Kulahci"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, New Jersey : , : Wiley, , 2015"]
[{"$nulls":4},"2015"]
[null,null,"ISBN",null,"1-118-74522-1"]
[null,null,"Edizione",null,"[Second edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (671 p.)"]
[null,null,"Collana",null,"Wiley Series in Probability and Statistics"]
[null,null,"Disciplina",null,"519.55"]
[null,null,"Soggetti",null,"Forecasting"]
[{"$nulls":4},"Time-series analysis"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Introduction to Time Series Analysis and Forecasting -- Contents -- Preface -- 1 Introduction to Forecasting -- 1.1 The Nature and Uses of Forecasts -- 1.2 Some Examples of Time Series -- 1.3 The Forecasting Process -- 1.4 Data for Forecasting -- 1.4.1 The Data Warehouse -- 1.4.2 Data Cleaning -- 1.4.3 Imputation -- 1.5 Resources for Forecasting -- Exercises -- 2 Statistics Background for Forecasting -- 2.1 Introduction -- 2.2 Graphical Displays -- 2.2.1 Time Series Plots -- 2.2.2 Plotting Smoothed Data -- 2.3 Numerical Description of Time Series Data -- 2.3.1 Stationary Time Series -- 2.3.2 Autocovariance and Autocorrelation Functions -- 2.3.3 The Variogram -- 2.4 Use of Data Transformations and Adjustments -- 2.4.1 Transformations -- 2.4.2 Trend and Seasonal Adjustments -- 2.5 General Approach to Time Series Modeling and Forecasting -- 2.6 Evaluating and Monitoring Forecasting Model Performance -- 2.6.1 Forecasting Model Evaluation -- 2.6.2 Choosing Between Competing Models -- 2.6.3 Monitoring a Forecasting Model -- 2.7 R Commands for Chapter 2 -- Exercises -- 3 Regression Analysis and Forecasting -- 3.1 Introduction -- 3.2 Least Squares Estimation in Linear Regression Models -- 3.3 Statistical Inference in Linear Regression -- 3.3.1 Test for Significance of Regression -- 3.3.2 Tests on Individual Regression Coefficients and Groups of Coefficients -- 3.3.3 Confidence Intervals on Individual Regression Coefficients -- 3.3.4 Confidence Intervals on the Mean Response -- 3.4 Prediction of New Observations -- 3.5 Model Adequacy Checking -- 3.5.1 Residual Plots -- 3.5.2 Scaled Residuals and PRESS -- 3.5.3 Measures of Leverage and Influence -- 3.6 Variable "]
[{"$nulls":4},"Selection Methods in Regression -- 3.7 Generalized and Weighted Least Squares -- 3.7.1 Generalized Least Squares -- 3.7.2 Weighted Least Squares -- 3.7.3 Discounted Least Squares."]
[{"$nulls":4},"3.8 Regression Models for General Time Series Data -- 3.8.1 Detecting Autocorrelation: The Durbin-Watson Test -- 3.8.2 Estimating the Parameters in Time Series Regression Models -- 3.9 Econometric Models -- 3.10 R Commands for Chapter 3 -- Exercises -- 4 Exponential Smoothing Methods -- 4.1 Introduction -- 4.2 First-Order Exponential Smoothing -- 4.2.1 The Initial Value, -- 4.2.2 The Value of l -- 4.3 Modeling Time Series Data -- 4.4 Second-Order Exponential Smoothing -- 4.5 Higher-Order Exponential Smoothing -- 4.6 Forecasting -- 4.6.1 Constant Process -- 4.6.2 Linear Trend Process -- 4.6.3 Estimation of -- 4.6.4 Adaptive Updating of the Discount Factor -- 4.6.5 Model Assessment -- 4.7 Exponential Smoothing for Seasonal Data -- 4.7.1 Additive Seasonal Model -- 4.7.2 Multiplicative Seasonal Model -- 4.8 Exponential Smoothing of Biosurveillance Data -- 4.9 Exponential Smoothers and Arima Models -- 4.10 R Commands for Chapter 4 -- Exercises -- 5 Autoregressive Integrated Moving Average (ARIMA) Models -- 5.1 Introduction -- 5.2 Linear Models for Stationary Time Series -- 5.2.1 Stationarity -- 5.2.2 Stationary Time Series -- 5.3 Finite Order Moving Average Processes -- 5.3.1 The First-Order Moving Average Process, MA(1) -- 5.3.2 The Second-Order Moving Average Process, MA(2) -- 5.4 Finite Order Autoregressive Processes -- 5.4.1 First-Order Autoregressive Process, AR(1) -- 5.4.2 Second-Order Autoregressive Process, AR(2) -- 5.4.3 General Autoregressive Process, AR() -- 5.4.4 Partial Autocorrelation Function, PACF -- 5.5 Mixed Autoregressive-Moving Average Processes -- 5.5.1 Stationarity of ARMA(p, q) Process -- 5.5.2 Invertibility of ARMA(p, q) Process -- 5.5.3 ACF and PACF of ARMA(p, q) Process -- 5.6 Nonstationary Processes -- 5.6.1 Some Examples of ARIMA(p, d, q) Processes -- 5.7 Time Series Model Building -- 5.7.1 Model Identification."]
[{"$nulls":4},"5.7.2 Parameter Estimation -- 5.7.3 Diagnostic Checking -- 5.7.4 Examples of Building ARIMA Models -- 5.8 Forecasting Arima Processes -- 5.9 Seasonal Processes -- 5.10 Arima Modeling of Biosurveillance Data -- 5.11 Final Comments -- 5.12 R Commands for Chapter 5 -- Exercises -- 6 Transfer Functions and Intervention Models -- 6.1 Introduction -- 6.2 Transfer Function Models -- 6.3 Transfer Function-Noise Models -- 6.4 Cross-Correlation Function -- 6.5 Model Specification -- 6.6 Forecasting with Transfer Function-Noise Models -- 6.7 Intervention Analysis -- 6.8 R Commands for Chapter 6 -- Exercises -- 7 Survey of Other Forecasting Methods -- 7.1 Multivariate Time Series Models and Forecasting -- 7.1.1 Multivariate Stationary Process -- 7.1.2 Vector ARIMA Models -- 7.1.3 Vector AR (VAR) Models -- 7.2 State Space Models -- 7.3 Arch and Garch Models -- 7.4 Direct Forecasting of Percentiles -- 7.5 Combining Forecasts to Improve Prediction Performance -- 7.6 Aggregation and Disaggregation of Forecasts -- 7.7 Neural Networks and Forecasting -- 7.8 Spectral Analysis -- 7.9 Bayesian Methods in Forecasting -- 7.10 Some Comments on Practical Implementation and Use of Statistical Forecasting Procedures -- 7.11 R Commands for Chapter 7 -- Exercises -- APPENDIX A Statistical Tables -- APPENDIX B Data Sets for Exercises -- APPENDIX C Introduction to R -- BASIC CONCEPTS IN R -- Bibliography -- Index -- EULA."]