This paper proposes an accurate confidence interval for the trend parameter in a linear regression model with long memory errors. The interval is based upon an equivalent sum of squares method and is shown to perform comparably to a weighted least squares interval. The advantages of the proposed interval lies in its relative ease of computation and should be attractive to practitioners.
Ko, Kyungduk; Lee, Jaechoul; and Lund, Robert. (2008). "Confidence Intervals for Long Memory Regressions". Statistics & Probability Letters, 78(13), 1894-1902. http://dx.doi.org/10.1016/j.spl.2008.01.057