1. A method for processing a global set of observations represented by a multivariate data set, comprising: identifying, from said global set of observations, a first observation; identifying, from said global set of observations, a first group of observations that are nearest to said first observation based on a distance metric; identifying said first observation as a first outlier observation if a residual of said first observation is statistically different from residuals of said first group of observations, wherein said residuals of said first observation and said first group of observations are determined based on a predictive model indicative of a global relationship between a response variable and at least one explanatory variables of said global set of observations; and storing an indication that said first observation is said first outlier observation when said residual of said first observation is statistically different from said residuals of said first group of observations.