Plot summary of results from multiple calls to UPSnnltd() and/or UPSivadj() after an initial setup call to UPSaccum(). The UPSgraph() plot displays any sensitivity of the LTD and LOA Distributions to choice of Number of Clusters in X-space.
UPSgraph(envir, nncol = "red", nwcol = "green3", ivcol = "blue", ...)name of the working local control classic environment.
optional; string specifying color for display of the Mean of the LTD distribution when weighted by cluster size from any calls to UPSnnltd().
optional; string specifying color for display of the Mean of the LTD distribution when weighted inversely proportional to variance from any calls to UPSnnltd().
optional; string specifying color for display of the Difference in LOA predictions, at PS = 100% minus that at PS = 0%, from any calls to UPSivadj().
Additional arguments to pass to the plotting function.
The third phase of Unsupervised Propensity Scoring is a graphical Sensitivity Analysis that depicts how the Overall Means of the LTD and LOA distributions change with the number of clusters.
Kaufman L, Rousseeuw PJ. (1990) Finding Groups in Data. An Introduction to Cluster Analysis. New York: John Wiley and Sons.
Obenchain RL. (2004) Unsupervised Propensity Scoring: NN and IV Plots. Proceedings of the American Statistical Association (on CD) 8 pages.
Obenchain RL. (2011) USPSinR.pdf USPS R-package vignette, 40 pages.
Rubin DB. (1980) Bias reduction using Mahalanobis metric matching. Biometrics 36: 293-298.