Smoothing, Forecasting and Prediction of Discrete Time Series (精装)

2004-6  

Dover Phoenix Ed (2004年6月10日)  

Robert Goodell Brown  

468  

Computer application techniques are applied to routine short-term forecasting and prediction in this classic of operations research. It covers a variety of integrated control systems typically used in indus-try and government procedures, tracing the development of practical techniques of routine short-term forecasting and emphasizing their roles in inventory and production and in fire control in air target tracking. The text begins with a consideration of data sources and sampling intervals, progressing to discussions of time series models and proba-bility models. An extensive overview of smoothing techniques sur-veys the mathematical methods for periodically raising the estimates of coefficients in forecasting problems. Sections on forecasting and error measurement and analysis are followed by an exploration of alternatives and the applications of the forecast to specific problems. A complete treatment of the handling of systems design problems ranges from observed data to decision rules. Nontechnical sum-maries accompany the presentation of each topic, and work sheets offer the option of hand computations that can be converted to com-puter programs. Mathematicians and systems designers will find this vo]ume a source of valuable and comprehensive material. Its complete development and discussion of the subject matter will benefit anyone seeking a thorough understanding of these techniques, particularly those who intend to apply its theoretical derivations to new areas.

1 IntrodnctlonSection Ⅰ Data　2 Sources of Data　3 The Sampling IntervalSection Ⅱ Models　4 Time Series Models　5 Probability ModelsSection Ⅲ Smoothing Techniques　6 Criteria　7 Exponential Smoothing　8 Choosing the Smoothing ConstantMultiple Smoothing for Higher-order Polynomials　10 Analysis of Characteristics　11 Adaptive Fitting of Transcendental Functions　12 General Exponential Smoothing　13 Probability ModelsSection Ⅳ Forecasting　14 Lead Times　15 Forecasting with Time-Series Models　16 Variances of Coefficients and Forecasts　17 Forecasting with Probability Models　18 Special Direct ForecastsSection Ⅴ Error Measurement and Analysis　19 The Normality of Forecast Errors　20 Forecasting the Allowance for Error　21 Optimum Linear FiltersSection Ⅵ Exploration of Alternatives　22 Work Sheets for Hand Computations　23 Planning the Exploration Program　24 Computer Simulation ProgramsSection Ⅶ Applications　25 Safety Factors |or Inventory Control　26 Rally HandicapsAppendixIndex

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