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J. R. Peterson (Columbia Astrophysics Laboratory), J. G. Jernigan (Berkeley Space Sciences Laboratory), S. M. Kahn (Columbia Astrophysics Laboratory)
We present a new method for analyzing multi-dimensional data. The method uses an astrophysical and instrument response Monte Carlo to simulate photons and then iteratively analyze the data. The simulated photons are then compared directly with the measured values for the data with a new multivariate generalization of the Cramér-von Mises and Kolmogorov-Smirnov statistic. Techniques for model fitting, error estimation, and deconvolution using this method are discussed. Examples of this approach using Chandra observations of X-ray clusters of galaxies and XMM-Newton Reflection Grating Spectrometer data are presented.