Multivariate Statistical Analysis of Low-voltage EDS Spectrum Images

Multivariate statistics applications in phase analysis of STEM-EDS spectrum images.

Spectrum imaging (SI) methods are displacing traditional spot analyses as the predominant paradigm for spectroscopic analysis with electron beam instrumentation. The multivariate nature of SI provides clear advantages for qualitative analysis of multiphase specimens relative to traditional gray-scale images acquired with non-spectroscopic signals, where different phases with similar average ato...

Modeling of Banks ‌Bankruptcy in Iran (Multivariate Statistical Analysis)

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 ...

Multivariate Statistical Analysis

Classical multivariate statistical methods concern models, distributions and inference based on the Gaussian distribution. These are the topics in the first textbook for mathematical statisticians by T.W. Anderson that was published in 1958 and that appeared as a slightly expanded 3rd edition in 2003. Matrix theory and notation is used there extensively to efficiently derive properties of the m...

Applied Multivariate Statistical Analysis

Interactive Analysis of Terabyte-sized SEM-EDS Hyperspectral Images

Scanning electron microscopy with energy-dispersive X-ray spectrometry (SEM-EDS) was used to characterize a macroscopic artifact from Peru (a Moche cast figure) [1]. A 3D hyperspectral datacube was acquired over 51.2 hours, measuring 11,520 x 9,984 pixels with 2,048 energy channels per pixel; each pixel corresponds to 900 nm in the x and y dimensions. With current technology, interacting with t...