Cargando…

Introduction to Time Series Analysis and Forecasting

Detalles Bibliográficos
Autor principal: Montgomery, Douglas C.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2015.
Colección:New York Academy of Sciences Ser.
Temas:
Acceso en línea:Texto completo

MARC

LEADER 00000cam a2200000Mu 4500
001 EBOOKCENTRAL_on1347028447
003 OCoLC
005 20240329122006.0
006 m o d
007 cr cnu||||||||
008 230209s2015 xx o ||| 0 eng d
040 |a EBLCP  |b eng  |c EBLCP  |d OCLCQ  |d OCLCO  |d EBLCP  |d OCLCQ  |d OCLCL  |d OCLCQ 
020 |a 9781118745229 
020 |a 1118745221 
035 |a (OCoLC)1347028447 
082 0 4 |a 519.5/5  |q OCoLC  |2 22/eng/20231120 
049 |a UAMI 
100 1 |a Montgomery, Douglas C. 
245 1 0 |a Introduction to Time Series Analysis and Forecasting  |h [electronic resource]. 
260 |a Newark :  |b John Wiley & Sons, Incorporated,  |c 2015. 
300 |a 1 online resource (671 p.). 
490 1 |a New York Academy of Sciences Ser. 
500 |a Description based upon print version of record. 
505 0 |a 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 
505 8 |a 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 
505 8 |a 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 Selection Methods in Regression -- 3.7 Generalized and Weighted Least Squares -- 3.7.1 Generalized Least Squares 
505 8 |a 3.7.2 Weighted Least Squares -- 3.7.3 Discounted Least Squares -- 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 
505 8 |a 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 
500 |a 5.3 Finite Order Moving Average Processes 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
655 0 |a Electronic books. 
758 |i has work:  |a Introduction to time series analysis and forecasting (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCFC8HrvwHP9R7Cq6gqFwJC  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Montgomery, Douglas C.  |t Introduction to Time Series Analysis and Forecasting  |d Newark : John Wiley & Sons, Incorporated,c2015  |z 9781118745113 
830 0 |a New York Academy of Sciences Ser. 
856 4 0 |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=7104020  |z Texto completo 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL7104020 
994 |a 92  |b IZTAP