A large deviations approach to error exponents in source coding and hypothesis testing

It is pointed out that the basic results can be proved fairly easily if one uses a Sanov theorem for the distribution of types. Such a theorem comes easily from large deviation theory. A caveat is that this technique only identifies the error exponent up to terms o(n) in the exponent, whereas the combinatorial arguments give an estimate up to terms O(log n) in the exponent