We introduce a semiparametric “tubular neighborhood” of a parametric model in the multinomial setting. It consists of all multinomial distributions lying in a distance-based neighborhood of the parametric model of interest. Fitting such a tubular model allows one to use a parametric model while treating it as an approximation to the true distribution. In this paper, the Kullback–Leibler distanc...

In this paper, we propose a novel approach to improve a statistical model-based voice activity detection (VAD) method based on a modified conditional maximum a posteriori (MAP) criterion incorporating the spectral gradient scheme. The proposed conditional MAP incorporates not only the voice activity decision in the previous frame as in [1] but also the spectral gradient of the observed spectra ...

In the inferential process of Principal Component Analysis (PCA), one main challenges for researchers is establishing correct number components to represent sample. For that purpose, heuristic and statistical strategies have been proposed. One approach consists in testing hypothesis equality smallest eigenvalues covariance or correlation matrix using a Likelihood-Ratio Test (LRT) follows χ2 lim...

We developed generalized functional linear models (GFLMs) to perform a meta-analysis of multiple case-control studies to evaluate the relationship of genetic data to dichotomous traits adjusting for covariates. Unlike the previously developed meta-analysis for sequence kernel association tests (MetaSKATs), which are based on mixed-effect models to make the contributions of major gene loci rando...

A validated simulation model primarily requires performing an appropriate input analysis mainly by determining the behavior of real-world processes using probability distributions. In many practical cases, probability distributions of the random inputs vary over time in such a way that the functional forms of the distributions and/or their parameters depend on time. This paper answers the quest...

The Middleton Class-A (MCA) model is one of the most widely applied models for narrow-band impulsive interference superimposed to additive white Gaussian noise (AWGN). The MCA noise process consists of an infinite number of Gaussian-distributed noise states with different variances. As a result, the optimum detector has irreducible form. Here, our analysis is based on a two-state model, where w...

Magnetic Resonance Force Microscopy (MRFM) is an emergent technology for measuring spin-induced attonewton forces using a micromachined cantilever. In the interrupted Oscillating Cantilever-driven Adiabatic Reversal (iOSCAR) method, small ensembles of electron spins are manipulated by an external radio frequency (RF) magnetic field to produce small periodic deviations in the resonant frequency ...

This paper aims to address the problem of profiling human activities captured in surveillance videos for the applications of online normal human activity recognition and anomaly detection. A novel framework is developed for automatic human activity modeling and online anomaly detection without any manual labeling of the training dataset. The framework consists of the following key components: 1...

In the paper by Jiang and Yang (2013), six classical Likelihood Ratio Test (LRT) statistics are studied under high-dimensional settings. Assuming that a random sample of size n is observed from a p-dimensional normal population, they derive the central limit theorems (CLTs) when p/n → y ∈ (0, 1], which are different from the classical chisquare limits as n goes to infinity while p remains fixed...

Three integration schemes, namely, coherent, noncoherent, and semi-coherent integration, and their variants are described in this paper for signal detection and tracking in such applications as pulsed Doppler radar and GPS receiver. We adopt a unified approach to present such integration schemes as best approximations to the likelihood ratio test (LRT) when the signal models are partially known...