Acoustic echo canceler and postfilter for residual echo suppression are two essential building blocks of a hands-free voice communication system. Based on the Kalman filter theory, we derive a simple and advanced algorithm for the optimum joint statistical adaptation of both filter coefficients in time-varying and noisy acoustic environments. The Kalmar filter utilizes a stochastic state-space model of the acoustic echo path which is formulated entirely in the frequency-domain. The resulting adaptive algorithm is computationally efficient and inherently robust, i.e., the adaptation does not require additional regularization or control mechanisms.