Robust multivariate analysis for mixed-type data: Novel algorithm and its practical application in socio-economic research

A Fuzzy C-means Algorithm for Clustering Fuzzy Data and Its Application in Clustering Incomplete Data

The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal fuzzy data. Then, as an application, a method based on the proposed algorithm is pres...

Synchrosqueezing-based Transform and its Application in Seismic Data Analysis

Seismic waves are non-stationary due to its propagation through the earth. Time-frequency transforms are suitable tools for analyzing non-stationary seismic signals. Spectral decomposition can reveal the non-stationary characteristics which cannot be easily observed in the time or frequency representation alone. Various types of spectral decomposition methods have been introduced by some resear...

Robust Evolutionary Algorithm Design for Socio-Economic Simulation: Some Comments

In the original papers by Alkemade et al. (2006, 2007), their evolutionary algorithms (EAs) exhibited an extreme degree of premature convergence when they were run according to approach I. This seemed a quite curious result. We are happy that the correction (Alkemade et al. 2008) makes clear that the degree of premature convergence is much lower than originally reported. There are three further...

MK-Prototypes: A Novel Algorithm for Clustering Mixed Type Data

How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification

Data with mixed-type (metric–ordinal–nominal) variables are typical for social stratification, i.e. partitioning a population into social classes. Approaches to cluster such data are compared, namely a latent class mixture model assuming local independence and dissimilarity-based methods such as k -medoids. The design of an appropriate dissimilarity measure and the estimation of the number of c...