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Recent Developments and Perspectives of Statistical Time Series Analysis

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*+*ffi t 1 ] Abraham, B. and Ledolter, J. (1986). Forecast functions implied by autoregressive integrated moving average models and other related forecast procedures,internat' Statist. Reu',54,51-66' l2) Ahn, S. K. (1ggg). Distribution for residual autocovariances in multivariate autoregressive models with structured parameterization, Biometrika, 75, 590-593. t 3 ] Akaike, H. (1962). On the design of lag window for the estimation of spectra, Ann. Inst' Statist' Math.,14,I-27. t 4 I Akaike, H. (1969). power spectrum estimation through autoregressive model fitting, Ann' Inst' Statistical Inference for Stochastic Processes, Asymptotic inference for stochastic processes, some statistical estimates of spectral density, Theory Probab. APpl', XXVII, 795-813' IZZ) Berk, K. N. (ig74). Consistent autoregressive spectral estimates, Ann- Statist',2,489-502' 124) Blackmann, R. B. and Tukey, J. W. (1958). The Measurement of Power Sbectra' Dover' ltsl Bloomfield, p. (1923). An exponential model for the spectrum of a scalar time series, Bi'ometrikn' 60,217-226. lzal Box, G. E. p. and Jenkins, G. M. (1976). Time Series Analysis ; Forecasting and Control, revised

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