China
Africa
Explore chapters and articles related to this topic
A Simple Algorithm to Estimate the 'Performance Centres' of India and their Movements using Geodetic Coordinates
Published in Purna Chandra Mishra, Muhamad Mat Noor, Anh Tuan Hoang, Advances in Mechanical and Industrial Engineering, 2022
These optimal centres are popularly known as the “Geometric Medians” and can be computed considering the distance, area, population (or) GDP as the ‘weights’. The administrative, manufacturing, warehouse or distribution centres may be established in these centres. If connectivity is critical, the access centre becomes important. Population centre becomes important, when the population plays an important role in making a decision and so on. In operations research, such problems can be handled by considering them as a Fermat-Weber problem [1]. Locating such a ‘Geometric Median’ is a kind of optimisation problem and has no analytical solution for more than four data points.
Phenomenological Creep Models of Fibrous Composites (Probabilistic Approach)
Published in Leo Razdolsky, Phenomenological Creep Models of Composites and Nanomaterials, 2019
The median of a random variable (Me) is its value x, for which the probability of the appearance of a random variable smaller than the median, or greater than the median, is the same: p (x < Me) ä p (x > Me). The geometric median is the abscissa of a point at which the area bounded by the distribution curve is divided in half.
Nonparametric Phase-II control charts for monitoring high-dimensional processes with unknown parameters
Published in Journal of Quality Technology, 2021
Amitava Mukherjee, Marco Marozzi
Noting that, in this article, we discuss interpoint distance with respect to a randomly chosen reference sample. Naturally, one may argue that it is better to use spatial median of the reference sample for computing the distances of reference and test samples. The spatial median, also known as geometric median (GM), is the point minimizing the sum of distances to a discrete set of sample points in the Euclidean space. Unlike origin, which may be far away from the data cluster, spatial median is certainly a better choice for computing distances. But the problem is, since spatial median is computed using all the reference sample, corresponding distances are not independent, which violates a major assumption of the two-sample rank-statistics considered in this paper. As a result, corresponding monitoring scheme will be nonparametric, but not purely distribution-free.
Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets
Published in Technometrics, 2018
Rajarshi Guhaniyogi, Sudipto Banerjee
A closed form expression for ‖pk − π*(m − 1)‖ρ is easily obtained by referring to the formula where and . z1i, z2i's are dummy variables representing atoms of Ω, are indicator functions at z1i, z2i, respectively. Weiszfeld's algorithm yields the geometric median of points lying on a separable Banach space.