Analytical expressions for the REM model of recognition memory

• An analytic, Fourier transform expression of the REM model of recognition memory is derived.
• The expression much reduces the time required to generate model predictions.
• The derivation shows that the memory vector length can strongly affect model predictions.

An inordinate amount of computation is required to evaluate predictions of simulation-based models. Following Myung et al. (2007), we derived an analytic form expression of the REM model of recognition memory using a Fourier transform technique, which greatly reduces the time required to perform model simulations. The accuracy of the derivation is verified by showing a close correspondence between its predictions and those reported in Shiffrin and Steyvers (1997). The derivation also shows that REM’s predictions depend upon the vector length parameter, and that model parameters are not identifiable unless one of the parameters is fixed.