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This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymp...
This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymp...
This paper investigates the quasi-maximum likelihood estimation of spatial dynamic panel data mod-els where spatial weights matrices can be time varying. We …nd that QML estimate is consistent and asy...
Recent analysis of Multiple-Input Multiple-Output (MIMO) communication systems, for example those involving antenna arrays, has shown that channel capacity increases linearly with the number of antenn...
This paper presents a new distributed power control algorithm for ad-hoc wire- less networks in random channel environments. Previous work in this area has focused on distributed power control for ad-...
This paper presents new distributed power and admission control algorithms for ad-hoc wireless networks in random channel environments. Previous work in this area has focused on distributed control fo...
We consider parameter estimation, hypothesis testing and vari-able selection for partially time-varying coefficient models. Our asymp-totic theory has the useful feature that it can allow dependent, n...
Signal estimation from incomplete observations improves as more signal structure can be exploited in the inference process. Classic algorithms (e.g., Kalman filtering) have exploited strong dynamic st...
The problem of test of fit for Vector AutoRegressive (VAR) processes with unconditionally heteroscedastic errors is studied. The volatility structure is deterministic but time-varying and allows for...
A trend in compressed sensing (CS) is to exploit struc- ture for improved reconstruction performance. In the basic CS model (i.e. the single measurement vec- tor model), exploiting the clustering s...
There exist very few results on mixing for non-stationary processes. However, mixing is often required in statistical inference for non-stationary processes such as time-varying ARCH (tvARCH) models. ...
Modeling viral dynamics in HIV/AIDS studies has resulted in a deep understanding of pathogenesis of HIV infection from which novel antiviral treatment guidance and strategies have been derived. Viral ...
This paper is devoted to ARMA models with timedependent coefficients, including well-known periodic ARMA models. We provide state-space representations and Kalman-type recursions to derive a Wold–C...
Due to the dynamic nature of biological systems, biological networks underlying temporal process such as the development of Drosophila melanogaster can exhibit signicant topological changes to facili...

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