The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians. Although the consistency of the nonparametric MLE is regarded as a standard conclusion, many researchers ignore the precise conditions required on the mixture model. An incorrect claim of consistency can lead to false conclusions even if the mixture model u...

A procedure for solving exact maximum likelihood estimation (MLE) is proposed for non-invertible non-Gaussian MA processes. By augmenting certain latent variables, the exact likelihood of all relevant innovations can be expressed explicitly according to a set of recursions (Breidt and Hsu, 2005). Then, the exact MLE is solved numerically by EM algorithm. Two alternative estimators are proposed ...

The blood flow in the human cardiovascular system obeys the laws of fluid mechanics. Investigation of the flow properties reveals that a correlation exists between the velocity in time and space. The possible changes in velocity are limited, since the blood velocity has a continuous profile in time and space. This paper presents a new estimator (STC-MLE), which incorporates the correlation prop...

β-glucan (BG) and mulberry have received increasing attention for their benefits as natural sources of metabolic health. In the current study, we investigated the synergetic beneficial effects of BG and mulberry leaf extract (MLE) in mice fed a high-fat diet (HFD). Male C57BL6 mice were fed a HFD for twelve weeks to induce significant obesity and insulin resistance. BG and MLE were administrate...

We suggest an iterative approach to computing K-step maximum likelihood estimates (MLE) of the parametric components in semiparametric models based on their profile likelihoods. The higher order convergence rate of K-step MLE mainly depends on the precision of its initial estimate and the convergence rate of the nuisance functional parameter in the semiparametric model. Moreover, we can show th...

The popular MLE (Maximum Likelihood Estimation) is a generative approach for acoustic modeling and ignores the information of other phones during training stage. Therefore, the MLE-trained acoustic models are confusable and unable to distinguish confusing phones well. This paper introduces discriminative measures of minimum phone/word error (MPE/MWE) to refine acoustic models to deal with the p...

BACKGROUND Topical steroid treatment induces diverse local Wand systemic adverse effects. Several approaches have been tried to reduce the steroid-induced adverse effects. Simultaneous application of physiological lipid mixture is also suggested. OBJECTIVE Novel vehicles for topical glucocorticoids formulation were evaluated for the efficacy of reducing side-effects and the drug delivery prop...

Exposure to bleomycin in rodents induces lung injury and fibrosis. Alveolar epithelial cell death has been hypothesized as an initiating mechanism underlying bleomycin-induced lung injury and fibrosis. In the present study we evaluated the contribution of mitochondrial and receptor-meditated death pathways in bleomycin-induced death of mouse alveolar epithelial cells (MLE-12 cells) and primary ...

Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn these models exactly, various approximate learning techniques have been developed, such as contrastive divergence (CD) and Markov chain Monte Carlo maximum likelihood estimation (MCMC-MLE). In this paper, we introduce...

When the spatial sample size is extremely large, which occurs in many environmental and ecological studies, operations on the large covariance matrix are a numerical challenge. Covariance tapering is a technique to alleviate the numerical challenges. Under the assumption that data are collected along a line in a bounded region, we investigate how the tapering affects the asymptotic efficiency o...