Rapid population growth as well as agricultural and industrial development have increased the contamination of Iranian rivers. This study utilized principal components analysis (PCA) to determine the degree of significance of qualitative parameters of water resources in the Karkheh River in southwestern Iran. Cluster analysis (CA) grouped the monitoring stations based on the water quality data ...

the objective of this study was to investigate the relationship among body weight and fat-tail measurements with fat-tail weight by using multiple regression and principal component analysis. the eleven characters includes, body weight, fat-tail length, fat-tail circumference, width and diameters in 3 position of upper, middle and lower before the slaughter, and also fat-tail weight after the s...

Detecting outlying observations is an important step in any analysis, even when robust estimates are used. In particular, the robustified Mahalanobis distance is a natural measure of outlyingness if one focuses on ellipsoidal distributions. However, it is well known that the asymptotic chi-square approximation for the cutoff value of the Mahalanobis distance based on several robust estimates (l...

We propose a principal components regression method based on maximizing joint pseudo-likelihood for responses and predictors. Our uses both predictors to select linear combinations of the relevant regression, thereby addressing an oft-cited deficiency conventional regression. The proposed estimator is shown be consistent in wide range settings, including ones with non-normal dependent observati...

Introduction of Human Development Index (HDI) by UNDP in early 1990 followed a surge in use of non-parametric and parametric indices for measurement and comparison of countries performance in development, globalization, competition, well-being and etc. The HDI is a composite index of three indicators. Its components are to reflect three major dimensions of human development: longevity, knowledg...