The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ' function, involving two hyperparameters. Our goal is to estimate the optimal parameters in order to automatically reconstruct images. We propose to use the Maximum Likelihood Estimator (MLE), applied to the observed image. We need sampling from prior a...

This study examined the laxative effects of mulberry leaf extract (MLE) fermented by lactic acid bacteria (LAB), which contains high levels of polyphenolic and flavonoid compounds, against loperamide-induced constipation in rats. Sprague-Dawley rats were divided into a normal group (N) and three experimental groups; loperamide treated group (C), loperamide and LAB-fermented MLE 300 mg/kg treate...

We study and compare three estimators of a discrete monotone distribution: (a) the (raw) empirical estimator; (b) the "method of rearrangements" estimator; and (c) the maximum likelihood estimator. We show that the maximum likelihood estimator strictly dominates both the rearrangement and empirical estimators in cases when the distribution has intervals of constancy. For example, when the distr...

0360-8352/$ see front matter Published by Elsevier doi:10.1016/j.cie.2010.01.008 q This manuscript was processed by Area Editor E.A * Tel.: +1 845 938 5988. E-mail address: [email protected] A variation of maximum likelihood estimation (MLE) of parameters that uses probability density functions of order statistic is presented. Results of this method are compared with traditional maximum like...

We describe an original implementation of k-Maximum Likelihood Estimator (k-MLE)[1], a fast algorithm for learning finite statistical mixtures of exponential families. Our version converges to a local maximum of the complete likelihood while guaranteeing not to have empty clusters. To initialize k-MLE, we propose a careful and greedy strategy inspired by k-means++ which selects automatically cl...

In this paper we introduce a weighted composite quantile regression (CQR) estimation approach and study its application in nonlinear models such as exponential models and ARCH type of models. The weighted CQR is augmented by using a data-driven weighting scheme. With the error distribution unspecified, the proposed estimators share robustness from quantile regression and achieve nearly the same...

The rank-based fit of a linear model is based on minimizing a norm. A score function needs to be selected for the fit and the proper choice leads to asymptotically efficient regression estimators, i.e., fits equivalent to the maximum likelihood estimators (mle). In this paper, we present the family of optimal scores functions for the skew-normal family of distributions. We show the easy computa...

Abstract In statistics it is necessary to study the relation among many probability distributions. Information geometry elucidates the geometric structure on the space of all distributions. When combined with Bayesian decision theory, it leads to the new concept of “ideal estimates”. They uniquely exist in the space of finite measures, and are generally sufficient statistic. The optimal estimat...

For centuries, mulberry leaf has been used in traditional Chinese medicine for the treatment of diabetes. This study aims to test the prevention effects of a proprietary mulberry leaf extract (MLE) and a formula consisting of MLE, fenugreek seed extract, and cinnamon cassia extract (MLEF) on insulin resistance development in animals. MLE was refined to contain 5% 1-deoxynojirimycin by weight. M...

PURPOSE Various therapeutic approaches have been suggested for preventing or reducing the adverse effects of topical glucocorticoids, including skin barrier impairment. Previously, we have shown that impairment of skin barrier function by the highest potency topical glucocorticoid, clobetasol 17-propinate (CP), can be partially prevented by co-application of a physiological lipid mixture contai...