Weak convergences of marked empirical processes with applications to goodness-of-fit tests for Markovian processes

In this paper, weak convergences of marked empirical processes in $L^2(\mathbb{R},\nu)$ and their applications to statistical goodness-of-fit tests are provided, where $L^2(\mathbb{R},\nu)$ is a set of equivalence classes of the square integrable functions on $\mathbb{R}$ with respect to a finite Borel measure $\nu$. The results obtained in our framework of weak convergences are, in the topological sense, weaker than those in the Skorokhod topology on a space of c\'adl\'ag functions or the uniform topology on a space of bounded functions, which have been well studied in previous works. However, our results have the following merits: (1) avoiding a smoothness condition which sometimes does not hold for some time series models appearing in statistics; (2) treating a weight function which make us possible to propose an Anderson--Darling type test statistics for goodness-of-fit tests. Indeed, the applications presented in this paper are novel.