Nonapproximability of the normalized information distance
Journal of Computer and System Sciences
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We study statistical sum-tests and independence tests, in particular for computably enumerable semimeasures on a discrete domain. Among other things, we prove that for universal semimeasures every $\Sigma ^{0}_{1}$-sum-test is bounded, but unbounded $\Pi ^{0}_{1}$-sum-tests exist, and we study to what extent the latter can be universal. For universal semimeasures, in the unary case of sum-test we leave open whether universal $\Pi ^{0}_{1}$-sum-tests exist, whereas in the binary case of independence tests we prove that they do not exist.