We introduce a goodness of fit test for ergodic Markov processes. Our test compares the data against the set of stationary densities implied by the class of models specified in the null hypothesis, and rejects if no model in the class yields a stationary density that matches with the data. No alternative needs to be specified in order to implement the test. Although our test compares densities it involves no smoothing parameters, and is powerful against 1/ n local alternatives

介绍了一种遍历马尔可夫过程的拟合优度检验方法。我们的测试将数据与零假设中指定的模型类别所隐含的固定密度集进行比较，如果该类中没有模型产生与数据匹配的固定密度，则拒绝。为了实现测试，不需要指定任何替代方案。虽然我们的测试比较密度，它不涉及平滑参数，并对1/ n局部替代是强大的