When incorrect prior statistics are used to implement sequential filtering algorithms, suboptimum performance and possibly filter divergence results. Thus it is desirable to estimate prior statistics from actual operating records and use these estimates in implementation of the optimum estimation algorithms. This paper presents a survey of currently existing algorithms for the sequential adaptive estimation of prior statistics.