Forecasting, methods and applications
Wiley, Apr 20, 1983 - Business & Economics - 923 pages
Presents a wide range of forecasting methods useful for undergraduate or graduate students majoring in business management, economics, or engineering. Develops skills for selecting the proper methodology. Integrates forecasting with the planning and decision-making activities within an organization. Methods of forecasting include: decomposition, regression analysis, and econometrics. Stresses the strengths and weaknesses of the individual methods in various types of organizational areas. Numerous examples are included.
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amplitudes applied approach ARIMA model ARRSES autocorrelation coefﬁcients autoregressive Box-Jenkins business cycle changes Chapter coefﬁcients column component computed conﬁdence correlation cross-correlations cyclical D(EOM data in Table data series deﬁned deﬁnition determine developed deviations differencing difﬁcult Durbin-Watson Statistic econometric models economic equation estimates example exponential smoothing factors ﬁgures ﬁnal ﬁnd ﬁrms ﬁrst differences ﬁt ﬁtting ﬁxed ﬂuctuations follows forecasting methods identiﬁed independent variables inﬂuence input series inventories leading indicator line spectrum linear linear regression mean methodology months moving average multicollinearity nonseasonal nonstationary output series parameters partial autocorrelations pattern percent period phase plot predict prewhitened procedure random ratio regression model regressors relevance trees residuals retail sample seasonally adjusted Section shows signiﬁcant signiﬁcantly different sine wave smoothing methods speciﬁc squared standard error stationary statistical time-series analysis transfer function model trend trend-cycle values variance weights wholesalers zero