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We consider a continuous-time model for inventory management with Markov mod-ulated non-stationary demands. We introduce active learning by assuming that the state of the world is unobserved and must ...
We analyze in this paper the asymptotic behavior of the specification test of Aït-Sahalia (1996) for the stationary density of a diffusion process, but when the diffusion is not stationary. We co...
In this article asymptotic expressions for the final prediction error (FPE) and the accumulated prediction error (APE) of the least squares predictor are obtained in regression models with nonstationa...
The superfamily phenomenon of time series with different dynamics can be charac-terized by the motif rank patterns observed in the nearest-neighbor networks of the time series in phase space. However,...
This paper studies functional coefficient regression models with nonstationary time series data, allowing also for stationary covariates. A local linear fitting scheme is developed to estimate the coe...
We analyze the question whether sliding window time averages applied to stationary increment processes converge to a limit in probability. The question centers on averages, correlations, and densities...
The method of cointegration in regression analysis is based on an assumption of stationary increments. Stationary increments with fixed time lag are called integration I(d). A class of regression mod...
It is ubiquitous in natural and social sciences that two variables, recorded temporally or spatially in a complex system, are cross-correlated and possess multifractal features. We propose a new meth...
This paper considers semiparametric estimation of a nonstationary transformation model with panel data. While nonstationarity is a common phenomenon in applied research, one of the drawbacks of most e...

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