In correspondence analysis, rows and columns of a data matrix are depicted as points in low-dimensional space. The row and column profiles are approximated by minimizing the so-called weighted chisquared distance between the original profiles and their approximations, see or example, Greenacre (1984). In this paper, we will study the inverse correspondence analysis problem, that is, the possibi...

Rosemary Kinuthia The Association between Female Genital Mutilation (FGM) and the Risk of HIV/AIDS in Kenyan Girls and Women (15-49 Years) (Under the direction of Dr. Ike S. Okosun, MS, MPH, PhD, FRSPH and Dr. Richard Rothenberg, MD, MPH, FACP). INTRODUCTION: Kenya like the rest of Sub-Saharan Africa continues to be plagued with high rates of AIDS/HIV. Research has shown that cultural practices...

We study the cosmology of a three-brane in specific five-dimensional scalar-gravity (i.e. soft-wall) background, known as linear dilaton background. discover that Friedmann equation brane-world automatically contains term mimicking pressureless matter. propose to identify this dark This matter arises projection bulk black hole on brane, which contributes brane via both Weyl tensor and scalar st...

Fuzzy C-Mean (FCM) is an unsupervised clustering algorithm based on fuzzy set theory that allows an element to belong to more than one cluster. Where fuzzy means “unclear” or “not defined” and c denotes “clustering”. In FCM the number of cluster are randomly selected. [15] FCM is the advanced version of K-means clustering algorithm and doing more work than K-means. K-Means just needs to do a di...

A family of dimension-reduction methods, the inverse regression (IR) family, is developed by minimizing a quadratic objective function. An optimal member of this family, the inverse regression estimator (IRE), is proposed, along with inference methods and a computational algorithm. The IRE has at least three desirable properties: (1) Its estimated basis of the central dimension reduction subspa...

Derivation of tight bounds for probability metrics and f -divergences is of interest in information theory and statistics. This paper provides elementary proofs that lead, in some cases, to significant improvements over existing bounds; they also lead to the derivation of some existing bounds in a simplified way. The inequalities derived in this paper relate between the Bhattacharyya parameter,...

Derivation of tight bounds for probability metrics and f -divergences is of interest in information theory and statistics. This paper provides elementary proofs that lead, in some cases, to significant improvements over existing bounds; they also lead to the derivation of some existing bounds in a simplified way. The inequalities derived in this paper relate between the Bhattacharyya parameter,...

The paper evaluates by means of Monte Carlo simulations the estimator of the regression coefficient obtained by the classical W-based spatial autoregressive model and the structural equations model with latent variables (SEM) on the basis of data sets that contain two types of spatial dependence: spillover from (i) a hotspot and (iia) first order queen contiguity neighbors or (iib) inverse dist...

BACKGROUND In the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1) and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nea...