1,490 research outputs found
Asymptotic inference in some heteroscedastic regression models with long memory design and errors
This paper discusses asymptotic distributions of various estimators of the
underlying parameters in some regression models with long memory (LM) Gaussian
design and nonparametric heteroscedastic LM moving average errors. In the
simple linear regression model, the first-order asymptotic distribution of the
least square estimator of the slope parameter is observed to be degenerate.
However, in the second order, this estimator is -consistent and
asymptotically normal for ; nonnormal otherwise, where and are
LM parameters of design and error processes, respectively. The
finite-dimensional asymptotic distributions of a class of kernel type
estimators of the conditional variance function in a more general
heteroscedastic regression model are found to be normal whenever ,
and non-normal otherwise. In addition, in this general model,
-consistency of the local Whittle estimator of based on pseudo
residuals and consistency of a cross validation type estimator of
are established. All of these findings are then used to propose a lack-of-fit
test of a parametric regression model, with an application to some currency
exchange rate data which exhibit LM.Comment: Published in at http://dx.doi.org/10.1214/009053607000000686 the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Spin transfer nano-oscillators
The use of spin transfer nano-oscillators (STNOs) to generate microwave
signal in nanoscale devices have aroused tremendous and continuous research
interest in recent years. Their key features are frequency tunability,
nanoscale size, broad working temperature, and easy integration with standard
silicon technology. In this feature article, we give an overview of recent
developments and breakthroughs in the materials, geometry design and properties
of STNOs. We focus in more depth on our latest advances in STNOs with
perpendicular anisotropy showing a way to improve the output power of STNO
towards the {\mu}W range. Challenges and perspectives of the STNOs that might
be productive topics for future research were also briefly discussed.Comment: 11 pages, 10 figures, nanoscale 201
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