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The likelihood ratio theory contributes tremendous success to para-metric inferences. Yet, there is no general applicable approach for non-parametric 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 "(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)
Many applications of nonparametric tests based on curve estimation involve selecting a smoothing parameter. The author proposes an adaptive test that combines several generalized likelihood ratio tests in order to get power performance nearly equal to whichever of the component tests is best. He derives the asymptotic joint distribution of the component(More)
Event-related functional magnetic resonance imaging (efMRI) has emerged as a powerful technique for detecting brains' responses to presented stimuli. A primary goal in efMRI data analysis is to estimate the Hemodynamic Response Function (HRF) and to locate activated regions in human brains when specific tasks are performed. This paper develops new(More)
AIMS Fascin-1, ezrin and paxillin, cytoskeleton-associated proteins, have been implicated in several human cancers, but their role in laryngeal squamous cell carcinoma (LSCC) is unknown. We investigated the association of their expression and clinicopathologic factors and their prognostic value in LSCC. MATERIALS AND METHODS Quantitative RT-PCR and(More)
Functional magnetic resonance imaging (fMRI) is emerging as a powerful tool for studying the process underlying the working of the many regions of the human brain. The standard tool for analyzing fMRI data is some variant of the linear model, which is restrictive in modeling assumptions. In this paper, we develop a semiparametric approach, based on the(More)