We consider the problem of estimation the population mean of the study variate Y in presence of measurement errors when information on an auxiliary character X is known. A class of estimators for population means using information on an auxiliary variate X is defined. Expressions for its asymptotic bias and mean square error are obtained. Optimum conditions are obtained for which the mean...

the decomposition $gamma=bh$ of a group $gamma$ into a subset $b$ and a subgroup $h$ of $gamma$ induces, under general conditions, a group-like structure for $b$, known as a gyrogroup. the famous concrete realization of a gyrogroup, which motivated the emergence of gyrogroups into the mainstream, is the space of all relativistically admissible velocities along with a binary operation given by t...

Résumé. Dans cet article, nous proposons un système de classification des comptes-rendus mammographiques, reposant sur une ontologie radiologique décrivant les signes radiologiques et les différentes classes de la classification ACR des systèmes BIRADS dans le langage OWL. Le système est conçu pour, extraire les faits issus des textes libres de comptes-rendus en étant dirigé par l’ontologie, pu...

BACKGROUND The rates of breast cancer have increased over the past two decades, and this raises concern about physical, psychological and social well-being of women with breast cancer. Further, few women really want to do breast cancer screening. We here investigated the socio-demographic correlates of mammography participation among 400 asymptomatic Iranian women aged between 35 and 69. METH...

The generation of random variates is an important tool that required in many applications. Various software programs or packages contain generators for standard distributions like the normal, exponential Gamma, e.g., programming language R and SciPy NumPy Python. However, it not uncommon sampling from new/non-standard required. Instead deriving specific such situations, so-called automatic blac...

The High-Dimensional Model Representation (HDMR) technique is a family of approaches to efficiently interpolate high-dimensional functions. RS(Random Sampling)-HDMR is a practical form of HDMR based on randomly sampling the overall function, and utilizing orthonormal polynomial expansions to approximate the RS-HDMR component functions. The determination of the expansion coefficients for the com...

Incorporating graph-based techniques in the analysis of multivariate signals is becoming a standard method to understand the interdependency of activity recorded at different sites. The new research frontier in this field includes the important problem of how to assess dynamic changes of signal activity. We present a unified framework of multivariate signals and network science through the grap...

This is a survey of the main methods in non-uniform random variate generation, and highlights recent research on the subject. Classical paradigms such as inversion, rejection, guide tables, and transformations are reviewed. We provide information on the expected time complexity of various algorithms, before addressing modern topics such as indirectly specified distributions, random processes, a...