Forecasting Economic Time SeriesIntroduction to the theory of time series; Spectral analysis; Building linear series models; The theory of forecasting; Practical methods for univariate time series forecasting; Forecasting from regression models; Multiple modeling and forecasting; The combination and evaluation of forecasting; Nonlinearity, nonstationarity, and other topics. |
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ae² arise in practice autocovariance autoregressive autoregressive process b)gc b₁ Box-Jenkins cause X coefficients conditional distribution function Consider correlation cost function C(e cost J given cumulative distribution function definition of causality denote derived deterministic components differencing Differentiating econometric econometricians equations estimated example exponential smoothing feedback follows forecast errors function of Xn+h Gaussian situation identification information set instantaneous causality interpreted as causality ity assumption linear cost function marginal costs marginal profit metric cost function moving average nonsymmetric cost functions normally distrib number of cakes observed obtained occur optimal forecast optimal predictor partial autocorrelations possible procedure purely nondeterministic series quadratic random variables residual series result roots of c(z sample autocorrelations Section stationary series stochastic processes structure substitution symmetric cost functions testable definition throwing a difficult uncorrelated unit circle uted variable values white noise process X₁ X₁+1 Xn+h given Y₁ zero zero-mean