In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

[Update: Within four weeks of the original publication of this research report, Risk Magazine reported in its 28th February 2012 issue story titled 'Goodbye VaR? Basel to Consider Other Risk Metrics': "A review of trading book capital rules, due to be launched in March by the Basel Committee on...

Poverty statistics are conventionally compiled using data from household income and expenditure survey or living standards survey. This study examines an alternative approach in estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial...

The spatial granularity of poverty statistics can have a significant impact on the efficiency of targeting resources meant to improve the living conditions of the poor. However, achieving granularity typically requires increasing the sample sizes of surveys on household income and expenditure or...

It is known that the service quality is considered a latent variable that is derived from the combination of some other independent latent variables (dimensions). The known variables (attributes), generally expressed by an ordinal scale, are observed by handing out questionnaires to the users of...

The concept of revealed comparative advantage (RCA) stands as a major pillar in empirical trade literature. Yet there is no absolute preference among the suggested RCA measures. Given that these are volume-based indices, results of any relevant empirical analysis would be heavily influenced by...

We propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order correction term is obtained from studying the estimator of the Gini index within a measurement error framework. In addition, it reveals an intuitive formula for the remaining...

This paper states that market sentiments are central to any financial data analysis. A vivid distinction is made between studying financial data in terms of the concept of volatility and in rapport to analysing financial data in terms of market sentiments. The former is an existing approach that...

This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis...

In this paper two indexes will be proposed. Customer Satisfaction of a service (e.g.: Degree Course) will be study through a "so called" formative model. It seems possible to breakdown the two indexes into three levels, which can be considered from bottom to top or crosswise, thus providing...