1. A system for performing computer aided flow cytometry experiments, the system comprising: detection electronics configured to obtain measurement data of a set of cytometric events for particles in a sample subjected to a flow cytometric experiment; a processor in data communication with the detection electronics, the processor configured to: obtain the measurement data; model the measurement data using a plurality of p-dimensional parametric distributions, the plurality of p-dimensional parametric distributions including at least a number, G, p-dimensional parametric distributions; provide an initial estimate of the parameters of said G p-dimensional parametric distributions; iteratively estimate updated parameters for each of the p-dimensional parametric distributions, wherein said estimating comprises: calculating, for each event, a posteriori probabilities that said event is a member of each of said parametric distributions, identifying a subset of said events that are within a neighborhood of at least one of said distributions based on a comparison of an event location to center points of respective distributions, wherein a number of events included in the identified subset of said events is less than a number of events in the set, and calculating, for each of the parameters for each of the p-dimensional parametric distributions, an updated estimate based on the calculated a posteriori probabilities for each event in the identified subset of said events, wherein said estimating is iterated at least once, and wherein subsequent calculation of the a posteriori probabilities is based on the updated estimate for the parameters; and after said iterative estimating, identify a gate indicating a population of the particles from each of the p-dimensional parametric distributions using the updated parameter estimates.