Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivariate data. It includes as a special case a method for recovering the unmixing matrix in independent components analysis (ICA). It also serves as a basis for classes of multivariate nonparametric tests, and as a tool in cluster analysis or blind discrimination. The aim of this paper is to briefly explain the (ICS) method and to illustrate how various applications can be implemented using the R package ICS. Several examples are used to show how the ICS method and ICS package can be used in analyzing a multivariate data set
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant coordinate selection (ICS) and projection pursuit (PP) are two methods that can be used to...
Background: The current gold standard in dimension reduction methods for high-throughput genotype da...
Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivar...
Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivar...
Invariant coordinate selection (ICS) has recently been introduced by Tyler et al. (2008) as a method...
Invariant Coordinate Selection (ICS) is a multivariate data transformation and a dimension reduction...
In high reliability standards fields such as automotive, avionics or aerospace, the detection of ano...
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Abstract: For last two decades, clustering is well-recognized area in the research field of data min...
A general method for exploring multivariate data by comparing different estimates of multivariate sc...
For multivariate data with noise variables, tandem clustering is a well-known technique that aims to...
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant coordinate selection (ICS) and projection pursuit (PP) are two methods that can be used to...
Background: The current gold standard in dimension reduction methods for high-throughput genotype da...
Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivar...
Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivar...
Invariant coordinate selection (ICS) has recently been introduced by Tyler et al. (2008) as a method...
Invariant Coordinate Selection (ICS) is a multivariate data transformation and a dimension reduction...
In high reliability standards fields such as automotive, avionics or aerospace, the detection of ano...
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Abstract: For last two decades, clustering is well-recognized area in the research field of data min...
A general method for exploring multivariate data by comparing different estimates of multivariate sc...
For multivariate data with noise variables, tandem clustering is a well-known technique that aims to...
Invariant Coordinate Selection (ICS) is a multivariate statistical method introduced by Tyler et al....
Invariant coordinate selection (ICS) and projection pursuit (PP) are two methods that can be used to...
Background: The current gold standard in dimension reduction methods for high-throughput genotype da...