title: An open-source software package for multivariate modeling and clustering: applications to air quality management.
abstract: This paper presents an open-source software package, rSCA, which is developed based upon a stepwise cluster analysis method and serves as a statistical tool for modeling the relationships between multiple dependent and independent variables. The rSCA package is efficient in dealing with both continuous and discrete variables, as well as nonlinear relationships between the variables. It divides the sample sets of dependent variables into different subsets (or subclusters) through a series of cutting and merging operations based upon the theory of multivariate analysis of variance (MANOVA). The modeling results are given by a cluster tree, which includes both intermediate and leaf subclusters as well as the flow paths from the root of the tree to each leaf subcluster specified by a series of cutting and merging actions. The rSCA package is a handy and easy-to-use tool and is freely available at http://cran.r-project.org/package=rSCA . By applying the developed package to air quality management in an urban environment, we demonstrate its effectiveness in dealing with the complicated relationships among multiple variables in real-world problems.
authors.affiliation: Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK, S4S 0A2, Canada.
authors.forename: Xiuquan
authors.initials: X
authors.lastname: Wang
authors.forename: Guohe
authors.initials: G
authors.lastname: Huang
authors.forename: Shan
authors.initials: S
authors.lastname: Zhao
authors.forename: Junhong
authors.initials: J
authors.lastname: Guo
mesh_terms: D016902:Air Pollution, Indoor; D016000:Cluster Analysis; D015233:Models, Statistical; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D012984:Software