Conformal testing: binary case with Markov alternatives
This work addresses incremental improvements in statistical testing methods for binary data with Markov dependencies, relevant for researchers in conformal prediction and hypothesis testing.
The authors tackled the problem of conformal testing for binary models under Markov alternatives to exchangeability, proposing two new classes of conformal test martingales, with one being statistically efficient and the other computationally efficient in experiments.
We continue study of conformal testing in binary model situations. In this note we consider Markov alternatives to the null hypothesis of exchangeability. We propose two new classes of conformal test martingales; one class is statistically efficient in our experiments, and the other class partially sacrifices statistical efficiency to gain computational efficiency.