Enables distribution inspection by visualization as described in [Thrun, 2018] and for example used in
InspectVariable(Feature, Name, i =1, xlim, ylim, sampleSize =1e+05, main)
Arguments
Feature: [1:n] Variable/Vector of Data to be plotted
Name: Optional, string, for x label
i: Optional, No. of variable/feature, an integer of the for lope
xlim: [2] Optional, range of x-axis for PDEplot and histogram
ylim: [2] Optional, range of y-axis, only for PDEplot
sampleSize: Optional, default(100000), sample size, if datavector is to big
main: string for the title if other than what is desribed in N
Author(s)
Michael Thrun
References
[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, doctoral dissertation 2017, Springer, ISBN: 978-3-658-20539-3, Heidelberg, 2018.
[Thrun/Ultsch, 2018] Thrun, M. C., & Ultsch, A. : Effects of the payout system of income taxes to municipalities in Germany, in Papiez, M. & Smiech,, S. (eds.), Proc. 12th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, pp. 533-542, Cracow: Foundation of the Cracow University of Economics, Cracow, Poland, 2018.
Examples
data("ITS")InspectVariable(ITS,Name='Income in EUR',main='ITS')