A Smoothed P-Value Test When There is a Nuisance Parameter under the Alternative

Abstract: We present a new test when there is a nuisance parameter under the alternative hypothesis. The test exploits the p-value occupation time [PVOT], the measure of the nuisance parameter subset on which a p-value test based on a a test statistic rejects the null hypothesis. Key contributions are: (i) An asymptotic critical value upper bound for our test is the significance level {\alpha}, making inference easy. (ii) We only require the test statistic to have a known or bootstrappable limit distribution, hence we do not require root(n)-Gaussian asymptotics, allowing for weak or non-identification, boundary values, heavy tails, infill asymptotics, and so on. (iii) A test based on the sup-p-value may be conservative and in some cases have trivial power, while the PVOT naturally controls for this by smoothing over the nuisance parameter space. Finally, (iv) the PVOT uniquely allows for bootstrap inference in the presence of nuisance parameters when some estimated parameters may not be identified.