Data consisting of time-indexed distributions cross-sectional or intraday returns have been extensively studied in finance, and provide one example which the data atoms consist serially dependent probability distributions. Motivated by such data, we propose an autoregressive model for density time series exploiting tangent space structure on that is induced Wasserstein metric. The densities the...

Chong (1995) and Bai (1997) proposed a sample-splitting method to estimate multiple-break model. However, their studies focused on stationary time series models, in which the identification of first break depends magnitude duration break, testing procedure is needed assist estimation remaining breaks subsamples split by points found earlier. In this paper, we focus nonstationary autoregressive ...

This paper considers the test of a unit root in transitional autoregressive models. In particular, we develop the asymptotic theory of the inf-t test for the null hypothesis of a unit root in a wide class of nonlinear autoregressive models having parameters that are identified only under the alternative of stationarity. Our framework is very general and allows for virtually all potentially inte...

Modeling spatial interactions that arise in spatially referenced data is commonly done by incorporating the spatial dependence into the covariance structure either explicitly or implicitly via an autoregressive model. In the case of lattice (regional summary) data, two common autoregressive models used are the conditional autoregressive model (CAR) and the simultaneously autoregressive model (S...

In this paper we address the problem of enhancing speech which has been degraded by additive noise. As proposed by Ephraim et al., autoregressive hidden Markov models (AR-HMM) for the clean speech and an autoregressive Gaussian for the noise are used. The filter applied to a given frame of noisy speech is estimated using the noise model and the autoregressive Gaussian having the highest a poste...

the price of oil plays an important role in the global economy and is an important factor influencing the government and commercial sectors. because of increasing importance of oil in financial markets, oil price predictions have always been an important subject for the researchers in economics, and other economic agents. this paper tries to study the behavior of crude oil prices based on smoot...