Forecasting: Methods and ApplicationsWiley, 20 de abr. de 1983 - 923 páginas 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. |
Conteúdo
2FUNDAMENTALS | 17 |
2FUNDAMENTALS OF QUANTITATIVE | 18 |
23624 | 34 |
Direitos autorais | |
24 outras seções não mostradas
Termos e frases comuns
amplitudes applied approach ARIMA model ARRSES autocorrelation coefficients b₁ Box-Jenkins business cycle changes Chapter column component computed correlation cross-correlations cyclical D(EOM Data Auto-correlation data in Table data points data series determine developed deviations differenced Durbin-Watson Statistic econometric models economic equation estimates example exponential smoothing F-test factors follows forecasting methods identify independent variables input series inventories Kalman filters leading indicator line spectrum linear linear regression MAPE mean methodology months moving average multicollinearity nonseasonal nonstationary output series parameters partial autocorrelations pattern percent period phase plot Power Spectrum predict prewhitened procedure r₁ random ratio regression model regressors residuals retail sample seasonally adjusted Section shows sine wave smoothing methods Spectrum Partials squared standard error stationary statistical time-series analysis transfer function model trend trend-cycle values variance weights wholesalers X₁ Y₁ zero Σχ