Chunming Zhang

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The likelihood ratio theory contributes tremendous success to parametric inferences. Yet, there is no general applicable approach for nonparametric inferences based on function estimation. Maximum likelihood ratio test statistics in general may not exist in nonparametric function estimation setting. Even if they exist, they are hard to find and can not be(More)
Time-homogeneous diffusion models have been widely used for describing the stochastic dynamics of the underlying economic variables. Recently, Stanton proposed drift and diffusion estimators based on a higher-order approximation scheme and kernel regression method. He claimed that “higher order approximations must outperform lower order approximations” and(More)
In an effort to capture the time variation on the instantaneous return and volatility functions, a family of time-dependent diffusion processes is introduced to model the term structure dynamics. This allows one to examine how the instantaneous return and price volatility change over time and price level. Nonparametric techniques, based on kernel(More)
The wide acceptance of bioinformatics, medical imaging and multimedia applications, which have a data-centric favor to them, require more efficient and application-specific systems to be built. Due to the advances in modern FPGA technologies recently, there has been a resurgence in research aimed at accelerator design that leverages FPGAs to accelerate(More)
The emergence of embedded and multimedia applications, which have a data-centric favor to them, have great influences on the design methodology of future systems. The 2D FFT is of particular importance to these applications. In this paper, leveraging the reconfigurable features of off-the-shelf FPGAs, we propose a stream architecture that is suitable for(More)
The problem of finding confidence regions for multiple predictor variables corresponding to given expected values of a response variable has not been adequately resolved. Motivated by an example from a study on hyperbaric exposure using a logistic regression model, we develop a conceptual framework for the estimation of the multi-dimensional effective dose(More)
It is widely known that, in a certain sense, a smoothing spline estimate of the regression function is asymptotically equivalent to a kernel regression estimate. However, little information has been available about the equivalence between nonparametric regression tests, based on the smoothing spline and local polynomial regression methods. To assess their(More)