Estimation of principal points for a multivariate binary distribution using a log-linear model

This article proposes a method for estimating principal points for a multivariate binary distribution, assuming a log-linear model for the distribution. Through numerical simulation studies, the proposed parametric estimation method using a log-linear model is compared with a nonparametric estimation method.     

The Methods for Approximation of Principal Points for Binary Distributions on the Basis of Submodularity

Principal points for binary distributions are able to be defined based on Flury’s principal points (1990 Flury, B.A. (1990). Principal points. Biometrica 77:33–41.[Crossref], [Web of Science ®] , [Google Scholar]). However, finding principal points for binary distributions is hard in a straightforward manner. In this article, a method for approximating principal points for binary distributions is proposed by formulating it as an uncapacitated location problem. Moreover, it is shown that the problem of finding principal points can be solved with the aid of submodular functions. It leads to a solution whose value is at least (1 ? 1/e) times the optimal value.     

Incremental optimization of independent sets under the reconfiguration framework

Journal of Combinatorial Optimization - Suppose that we are given an independent set $$I_0$$ of a graph G, and an integer $$l\ge 0$$ . Then, we are asked to find an independent set of G having the...     

A statistical test for the hypothesis of Gaussian random function

A Gaussian random function is a functional version of the normal distribution. This paper proposes a statistical hypothesis test to test whether or not a random function is a Gaussian random function. A parameter that is equal to 0 under Gaussian random function is considered, and its unbiased estimator is given. The asymptotic distribution of the estimator is studied, which is used for constructing a test statistic and discussing its asymptotic power. The performance of the proposed test is investigated through several numerical simulations. An illustrative example is also presented.