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

出版时间：2004-6  出版社：Dover Phoenix Ed (2004年6月10日)  作者：Robert Goodell Brown  页数：468  

内容概要

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.

书籍目录

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