Cluster Analysis of Per Capita Gross Domestic Products

Abstract

A B S T R A C T Objective:The purpose of this article is to show the value of exploratory data analysis performed on the multivariate time series dataset of gross domestic products per capita (GDP) of 160 countries for the years 1970-2010. New knowledge can be derived by applying cluster analysis to the time series of GDP to show how patterns in GDP can be explained in a data-driven way. Research Design & Methods:Patterns characterised by distance and density based structures were found in a topographic map by using dynamic time warping distances with the Databionic swarm (DBS) 1 . The topographic map represents a 3D landscape of data structures. Looking at the topographic map, the number of clusters was derived. Then, a DBS clustering was performed and the quality of the clustering was verified. Findings: Two clusters are identified in the topographic map. The rules deduced from classification and regression tree (CART) show that the clusters are defined by an event occurring in 2001 at which time the world economy was experiencing its first synchronised global recession in a quarter-century. Geographically, the first cluster mostly of African and Asian countries and the second cluster consists mostly of European and American countries. Implications & Recommendations: DBS can be used even by non-professionals in the field of data mining and knowledge discovery. DBS is the first swarm-based clustering technique that shows emergent properties while exploiting concepts of swarm intelligence, self-organisation, and game theory.

A Bioinformatics View on Acute Myeloid Leukemia Surface Molecules by Combined Bayesian and ABC Analysis

“…CD88 (C5AR1) has been reported to be expressed in AML cell lines and primary patient blasts and to contribute to cell motility [ 30 ], illustrating its potential role in this disease. We attribute the conflicting results for CD88 expression, as well as the overall lack of consistent observations, to the different molecular techniques for gene expression measurement [ 74 ], as Bayesian analysis based on GMMs has been shown to yield stable and consistent results on noisy data of various types, such as income, heat or cold pain, GDP time series or nitrate concentrations in streams [ 15 , 75 , 76 ]. Of note, the dataset of only 15 cases of APL samples is small, but in line with the reported frequency of this subgroup.…”