Normal view MARC view

Forecasting: methods and applications

Author: Wheelwright, Steven C. ; Makridakis, SpyrosINSEAD Area: Technology and Operations Management Series: Wiley/Hamilton series in management and administration Publisher: Wiley, 1978.Language: EnglishDescription: 713 p. : Graphs ; 24 cm.ISBN: 0471937703Type of document: INSEAD BookBibliography/Index: Includes bibliographical references and index
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Item type Current location Collection Call number Status Date due
INSEAD Book Doriot Library
Main Collection
Print HD30.27 .M34 1978
(Browse shelf)
001301304
Available
INSEAD Book Doriot Library
Main Collection
Print HD30.27 .M34
(Browse shelf)
000159503
Available

Includes bibliographical references and index

Digitized

Forecasting
Methods and Applications
Contents
Preface
PART ONE BACKGROUND AND PERSPECTIVE2
CHAPTER 1 INTRODUCTION4
1.1 Needs and Uses of Forecasting4
1.2 Current Status of Quantitative and Technological Forecasting7
References and Selected Bibliography12
CHAPTER 2 FUNDAMENTALS OF QUANTITATIVE FORECASTING14
2.1 Explanatory versus Time-Series Forecasting14
2.2 Least Squares Estimates17
2.3 Discovering and Describing Existing Relationships23
2.4 Variances and Covariances28
2.5 Autovariance and Autocorrelation34
Appendix Chapter 236
References and Selected Bibliography39
Exercises39
PART TWO SMOOTHING AND DECOMPOSITION
TIME-SERIES METHODS42
CHAPTER 3 SMOOTHING METHODS44
3.1 Introduction44
3.2 Single Moving Averages45
3.3 Single Exponential Smoothing48
3.4 Adaptive-Response-Rate Single Exponential Smoothing53
3.5 Linear Moving Averages55
3.6 Linear Exponential Smoothing61
3.7 Brown's Quadratic Exponential Smoothing66
3.8 Selecting the Appropriate Smoothing Method for the Data Pattern69
3.9 Winters' Linear and Seasonal Exponential Smoothing72
3.10 Other Smoothing Methods74
3.11 General Aspects of Smoothing Methods77
3.12 Development of the Mathematical Basis of Smoothing Methods79
References and Selected Bibliography81
Exercises82
CHAPTER 4 DECOMPOSITION METHODS88
4.1 Introduction88
4.2 Trend Fitting93
4.3 The Ratio-to-Moving Averages Classical Decomposition Method94
4.4 Different Types of Moving Averages101
4.5 The Census H Decomposition Method106
4.6 The FORAN System138
References and Selected Bibliography140
Exercises140
PART THREE REGRESSION METHODS144
CHAPTER 5 SIMPLE REGRESSION146
5.1 General Comments on Regression Methods146
5.2 Different Forms of Functional Relationships147
5.3 Determining the Parameters, a and b, of a Straight Line150
5.4 The Correlation Coefficient153
5.5 The Significance of a Regression Equation155
5.6 Trend Analysis, Time-Series Forecasting164
5.7 The Regression Equation as a Model165
Appendix Mathematical Supplement Chapter 5167
References and Selected Bibliography176
Exercises176
CHAPTER 6 MULTIPLE REGRESSION180
6.1 Introduction180
6.2 Applying Multiple Regression182
6.3 Multiple Correlation and the Coefficient of Determination183
6.4 Tests of Significance184
6.5 Transformations186
6.6 The Assumptions of Regression Analysis205
6.7 Multicollinearity209
6.8 Model Specification211
6.9 Lagged Variables216
6.10 Dummy Variables217
6.11 Summary220
Appendix Mathematical Supplement Chapter 6221
References and Selected Bibliography226
Exercises226
CHAPTER 7 ECONOMETRIC MODELS AND FORECASTING230
7.1 The Basis of Econometric Modeling231
7.2 The Advantages and Drawbacks of Econometric Methods233
7.3 Estimation Procedures Used by Econometric Models234
7.4 Specification and Identification238
7 5 Development and Application of Econometric Models240
References and Selected Bibliography248
PART FOUR AUTOREGRESSIVE/MOVING AVERAGE (ARMA)
TIME-SERIES METHODS250
CHAPTER 8 TIME-SERIES ANALYSIS252
8.1 Introduction to Autoregressive Schemes252
8.2 Identifying the Characteristics of a Time Series254
8.3 Autocorrelation Coefficients255
8.4 The Sampling Distribution of Autocorrelations258
8.5 Autocorrelation Analysis260
8.6 The x2-Test269
8.7 Partial Autocorrelations270
8.8 Summary of Time-Series Analysis271
References and Selected Bibliography273
Exercises273
CHAPTER 9 GENERALIZED ADAPTIVE FILTERING276
9.1 Analyzing and Forecasting a Time Series276
9.2 Autoregressive Models284
9.3 The Method of Adaptive Filtering286
9.4 Moving Average Models294
9.5 Applying the Method of Adaptive Filtering in MA Models296
9.6 Mixed Autoregressive Moving Average Models299
9.7 Seasonal ARMA Models307
9.8 Summary Comments on Generalized Adaptive Filtering309
Appendix Mathematical Supplement Chapter 9310
References and Selected Bibliography326
Exercises326
CHAPTER 10 THE BOX-JENKINS METHOD328
10.1 Identification328
10.2 Estimating the Parameters of an ARMA Model340
10.3 Diagnostic Checking of the Estimated Model342
10.4 Using an ARMA Model to Forecast344
10.5 Seasonal ARMA Models346
10.6 An Application of Seasonal ARMA Processes351
10.7 Achieving Stationarity in Variance361
References and Selected Bibliography368
Exercises369
CHAPTER 11 MULTIVARIATE TIME-SERIES ANALYSIS376
11.1 Introduction376
11.2 Bivariate Time-Series Analysis377 11.3 Identification of an Appropriate MARMA Model and Initial
Estimation of Its Parameters382 11.4 Estimation of the Parameters of a Specific MARMA Model
and Diagnostic Checking406 11.5 Identification of r, s, and b by Contracting the Cross
Autocorrelations of the Estimates419
11.6 Other Multivariate Models422
11.7 Conclusions428
References and Selected Bibliography430
PART FIVE QUALITATIVE AND TECHNOLOGICAL METHODS432
CHAPTER 12 PREDICTING THE CYCLE434
12.1 Introduction434
12.2 Business Cycles437
12.3 Causes of Business Cycles440
12.4 Anticipatory Surveys441
12.5 Leading Indicators443
12.6 Paired Indices443
12.7 Tracking the Evolution of Cycles451
References and Selected Bibliography455
CHAPTER 13 SUBJECTIVE ASSESSMENT METHODS456
13.1 The Basic Framework of Decision Analysis458
13.2 Methods for Obtaining Subjective Assessments464
13.3 Combining Subjective Assessments and Decision Analysis
in Practice476
References and Selected Bibliography485
Exercises485
CHAPTER 14 QUALITATIVE AND TECHNOLOGICAL METHODS OF FORECASTING492
14.1 I ntroduction492
14.2 Exploratory Methods of Forecasting494
14.3 Normative Approaches to Technological Forecasting514
14.4 Summary524
References and Selected Bibliography526
Exercise528
PART SIX INTEGRATING FORECASTING AND PLANNING
IN THE ORGANIZATION530
CHAPTER 15 FORECASTING AND PLANNING532
15.1 The Role of Forecasting in Planning532
15.2 Relating Forecasting and Planning in the Organization535
15.3 Forecasting as Input to Planning and Decision Making541
15.4 Contribution of Forecasting to Analysis and Understanding555
References and Selected Bibliography564
CHAPTER 16 COMPARISON AND SELECTION OF FORECASTING METHODS566
16.1 The Accuracy of Forecasting Methods568 16.2 Pattern of the Data and Its Effects on Individuai Forecasting
Methods587
16.3 Time Horizon Effects on Forecasting Methods588
16.4 The Costs of Forecasting Methods592
16.5 The Ease of Application of Forecasting Methods596 16.6 An Interactive Procedure for Selecting, Running, and
Comparing Alternative Forecasting Methods596
References and Selected Bibliography598
CHAPTER 17 DATA PROCUREMENT, PREPARATION, AND HANDLING600
17.1 Definition and Specification of Variables in Forecasting601
17.2 Data Procurement606
17.3 Data Preparation614
17.4 Data Management621
References and Selected Bibliography631
CHAPTER 18 ORGANIZATIONAL AND BEHAVIORAL ASPECTS OF FORECASTING632
18.1 Status of Forecasting in Business Firms633 18.2 Reasons for the Organizational Status of Forecasting
in the Mid-1970s642
18.3 Organizational Steps for Improved Forecasting649
18.4 Organizing for Individuai Forecasting Projects663
References and Selected Bibliography667
APPENDIX I STATISTICAL TABLES668
A Areas under the Normal Curve668
B Student t Distribution669
C Values of the F-Test670
D Values of the Durbin-Watson Statistic674
E Criticai Points of the Chi-Squared (x2) Statistic675
APPENDIX II GLOSSARY676
APPENDIX III DATA SOURCES698
INDEX703

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