1. A deviation detection method for use with a processing system including at least one processor, the method comprising: (a) receiving, at the processing system, at least one stream of event data from a machine that is generating events for the stream of event data, the event data including at least one attribute of performance of a task by the machine; (b) calculating, via the at least one processor, a long-term value by using a first estimate of a long-term probability density function (PDF) of the at least one monitored attribute in the at least one stream of event data over a long-term time window of the stream of event data; (c) calculating, via the at least one processor, a short-term value by using a second estimate of a short-term PDF of the at least one monitored attribute in the at least one stream of event data over a short-term time window that is of a shorter duration than the long-term time window; (d) computing, via the at least one processor, a first difference value between the calculated long-term value and an ideal density distribution value; (e) computing, via the at least one processor, a second difference value between the calculated short-term value and the ideal density distribution value; (f) computing, via the at least one processor, a current deviation as a function of the first difference value and the second difference value; (g) comparing the current deviation to a threshold value; (h) in response to the comparison of the current deviation exceeding the threshold value, triggering, in real-time with reception of the event stream, an adjustment in performance of the task being performed by the machine; and repeating (a)-(h) as further monitored events are generated by the machine for performance of the task and provided by the at least one stream of event data.