Prediction of LOD Change Based on the LS and AR Model with Edge Effect Corrected

Aiming to resolve the edge effect in the process of predicting length of day(LOD) by the least squares and autoregressive(LS+AR) model,we employed a time series analysis model to extrapolate LOD series and produce a new series.Then,we used the new series to solve the coefficients for the LS model.At last,we used the LS+AR model to predict the LOD series again.By comparing the accuracy of LOD prediction by edge-effect corrected LS+AR and that by LS+AR,we conclude that edge-effect corrected LS+AR can improve the prediction accuracy,especially for medium-term and long-term predictions.