A parametric regression model for right-censored data with a log-linear median regression function and a transformation in both response and regression parts, named parametric Transform-Both-Sides (TBS) model, is presented. The TBS model has a parameter that handles data asymmetry while allowing various different distributions for the error, as long as they are unimodal symmetric distributions ...

The purpose of this paper is to show the capacity of a new non-parametric test based on symbolic entropy and symbolic dynamics to deal with the detection of linear and non-linear spatial causality. The good performance of the new test in detecting spatial causality and causal weighting matrix is notable and gives rise to an expectation that it may form a adequate tool for constructive specifica...

In this paper, we will discuss the approaches and technologies associated with the development of the Geometry-Grid Toolkit (GGTK) and MiniCAD. GGTK is a software library that provides core functionalities in geometry, topology and mesh generation and MiniCAD is a software system with graphical user interface built on top of GGTK. The application of GGTK/MiniCAD to the development of customized...

A parametric manifold can be viewed as the manifold of orbits of a (regular) foliation of a manifold by means of a family of curves. If the foliation is hypersurface orthogonal, the parametric manifold is equivalent to the 1-parameter family of hypersurfaces orthogonal to the curves, each of which inherits a metric and connection from the original manifold via orthogonal projections; this is th...

Dynamic geometry systems are computer applications allowing the exact on– screen drawing of geometric diagrams and their interactive manipulation by mouse dragging. Whereas there exists an extensive list of 2D dynamic geometry environments, the number of 3D systems is reduced. Most of them, both in 2D and 3D, share a common approach for the management of geometric constructions, using numerical...

Nonparametric and parametric approaches have been proposed to estimate false discovery rate under the independent hypothesis testing assumption. The parametric approach has been shown to have better performance than the nonparametric approaches. In this article, we study the nonparametric approaches and quantify the underlying relations between parametric and nonparametric approaches. Our study...

In this paper an algorithm is presented for deriving the explicit robust model based optimal control law. The system is represented by linear, discrete-time, timeinvariant model with constraints on control and state variables and a quadratic objective function. Using the fundamentals of flexibility analysis the algorithm proposed in this paper derives the robust optimal control law off-line as ...

A new method of parametrio ooding at medium output rate is introduoed. The availability of new eleotronio oomponents ohanges the hypotheses assumed in previous studies. A parametrio ooding soheme with medium output rate is rendered feasible for rulebased synthesis, like for voioe-mailing systems. The weak spot in most of the parametrio synthesizers lies in the distinotion made between voioed an...

A numerical algorithm for effective incorporation of parametric uncertainty into mathematical models is presented. The uncertain parameters are modeled as random variables, and the governing equations are treated as stochastic. The solutions, or quantities of interests, are expressed as convergent series of orthogonal polynomial expansions in terms of the input random parameters. A high-order s...

In this paper we discuss how to deal with decision problems that are described with LP models and formulated with elements of imprecision and uncertainty. More precisely, we will study LP models in which the parameters are not fully known but only with some degree of precision. Even with incomplete information the model builder (or model user) is normally able to give a realistic interval for t...