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To estimate the parameters of a stationary univariate fractionally integrated time series, the unconditional exact likelihood function is derived. This allows the simultaneous estimation of all the parameters of the model by exact maximum likelihood. Issues involved in obtaining maximum likelihood estimates are discussed. Particular attention is given to efficient procedures to evaluate the likelihood function, obtaining starting values, and the small sample properties of the estimators. Limitations of previous estimation procedures are also discussed.