AbstractAcceptance of the adaptive-filtering parameter-estimation process has been mixed. Much of the variability between studies may result from the particular learning factor selected and may be further affected by the type of standardization used. The author presents a modification of the Makridakis and Wheelwright adaptive-filtering algorithm. This modified algorithm provides superior performance and simplifies the selection of the learning factor when used with simple autoregressive processes.