Remigijus Leipus

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The paper is concerned with the estimation of the long memory parameter in a conditionally heteroskedastic model proposed by Giraitis et al. (1999b). We consider estimation methods based on the partial sums of the squared observations, which are similar in spirit to the classical R/S analysis, as well as spectral domain approximate maximum likelihood(More)
We suggest a rescaled variance type test for stationarity (null hypothesis) against deter-ministic trends and unit roots. The asymptotic (parameter free) distribution of the test is derived and critical values tabulated by simulations for a wide class of stationary errors with short, long or negative dependence structure. The proposed test detects a(More)
The paper studies the aggregation/disaggregation problem of random parameter AR(1) processes and its relation to the long memory phenomenon. We give a characterization of a subclass of aggre-gated processes which can be obtained from simpler, " elementary " , cases. In particular cases of the mixture densities, the structure (moving average representation)(More)
The paper concerns the asymptotic distribution of the mixture density estimator, proposed by Leipus et al. (2006), in the aggrega-tion/disaggregation problem of random parameter AR(1) process. We prove that, under mild conditions on the (semiparametric) form of the mixture density, the estimator is asymptotically normal. The proof is based on the limit(More)