In this paper, we present a statistical approach for phoneme extraction based on universal constraint. Inspired by former phonological studies, we assume a fictitious point in each phoneme that exhibits the most stable information to explain the phoneme’s existence. With the universal constraint of phoneme definitions, the point is statistically estimated by an iterative procedure to maximize t...

the paper presents a possibility formulation of oneparameter estimation that unifies some usual probability formulations. Point and confidence interval estimation are unified in a single theoretical formulation and incorporated into estimators of an omnibus form: a possibility distribution. New relationships between continuous possibility distribution and probability concepts are established. T...

We analyze the predictive performance of various volatility models for stock returns. To compare their performance, we choose loss functions for which volatility estimation is of paramount importance. We deal with two economic loss functions (an option pricing function and an utility function) and two statistical loss functions (a goodness-of-fit measure for a Value-at-Risk (VaR) calculation an...

Utility estimators predict the usefulness or utility of a distorted natural image when used as a surrogate for a reference image. They differ from quality estimators in that they should provide accurate estimates even when images are extremely visibly distorted relative to the original, yet are still sufficient for the task. Our group has previously proposed the Natural Image Contour Evaluation...

Shape-constrained estimation techniques such as convex regression or log-concave density estimation offer attractive alternatives to traditional nonparametric methods. Shape-constrained estimation often has an easyto-optimize likelihood, no tuning parameter, and an adaptivity property where the sample complexity adapts to the complexity of the underlying functions. In this dissertation, we posi...

In this paper, the statement and the methods for solving the comparison-based structure-parametric identification problem of multifactor estimation model are addressed. A new method that combines heuristics methods with genetic algorithms is proposed to solve the problem. In order to overcome some disadvantages of using the classical utility functions, the use of nonlinear Kolmogorov-Gabor poly...

We consider an investor who faces parameter uncertainty in a continuous-time financial market. We model the investor’s preference by a power utility function leading to constant relative risk aversion. We show that the loss in expected utility is large when using a simple plug-in strategy for unknown parameters. We also provide theoretical results that show the trade-off between holding a well-...

Taking into account competitive markets, manufacturers attend more customer’s personalization. Accordingly, build-to-order systems have been given more attention in recent years. In these systems, the customer is a very important asset for us and has been paid less attention in the previous studies. This paper introduces a new build-to-order problem in the supply chain. This study focuses on bo...