in order to avoid drought effects, it is essential to detect and monitor the spatial andtemporal changes of the phenomenon. in general, drought indices are made use of toachieve the goals. the main aim followed in this paper is to introduce and assess a newdrought index termed mrdi. mrdi (modified reconnaissance drought index) is thencompared with modified standardized precipitation index (mspi...

In this paper we construct a modeling for detection of banks which are experiencing serious problems. Sample and variable set of the study contains 30 banks of Iran during 2006-2014 and their financial ratios. Well known multivariate statistical technique (principal component analysis) was used to explore the basic financial characteristics of the banks, and discriminant Logit and Probit models ...

We provide statistical and computational analysis of sparse Principal Component Analysis (PCA) in high dimensions. The sparse PCA problem is highly nonconvex in nature. Consequently, though its global solution attains the optimal statistical rate of convergence, such solution is computationally intractable to obtain. Meanwhile, although its convex relaxations are tractable to compute, they yiel...

Principal Component Analysis (PCA) is a classical technique in statistical data analysis, feature extraction and data reduction, aiming at explaining observed signals as a linear combination of orthogonal principal components. Independent Component Analysis (ICA) is a technique of array processing and data analysis, aiming at recovering unobserved signals or 'sources' from observed mixtures, ex...

In this paper, the spectral dimensions of two sets of samples including 457 black and 84 white fabrics are compared. White fabrics are treated with variety of fluorescent whitening agents and the blacks are fabrics that dyed with different combinations of suitable dyes and pigments. In this way, the reflectance spectra of blacks as well as the total radiance factors of whites are compressed in ...

Sparse principal component analysis (PCA) involves nonconvex optimization for which the global solution is hard to obtain. To address this issue, one popular approach is convex relaxation. However, such an approach may produce suboptimal estimators due to the relaxation effect. To optimally estimate sparse principal subspaces, we propose a two-stage computational framework named “tighten after ...

The balanced scorecard has proved itself as a valuable strategic tool in measuring not only the financial performance, but also the customer focus, internal business processes and learning and growth of a company. To date, very little has been done to incorporate new breakthroughs in financial management in the financial perspective of the balanced scorecard. In this study, new trends in financ...