  We present random sampling procedures for Motzkin and Schr\"oder paths,
following previous work on Dyck paths. Our algorithms follow the anticipated
rejection method of the Florentine algorithms (Barcucci et al. 1994+), but
introduce a recovery idea to greatly reduce the probability of rejection. They
use an optimal amount of randomness and achieve a better time complexity than
the Florentine algorithms.
