Non-Parametric Recurrent Events Data Analysis: Difference between revisions

Latest revision as of 10:53, 25 June 2012

Redirect to:

@@ Line 1: / Line 1: @@
-{{{{Non-Parametric Recurrent Events Data Analysis}}
+#REDIRECT [[Recurrent_Event_Data_Analysis]]
-==Non-Parameteric Recurrence Data Analysis==
-===Introduction===
-Non-parametric recurrence data analysis provides a nonparametric graphical estimate of the mean cumulative number or cost of recurrence per unit versus age. In the reliability field, the Mean Cumulative Function (MCF) can be used to: [31]
-:•	Evaluate whether the population repair (or cost) rate increases or decreases with age (this is useful for product retirement and burn-in decisions).
-:•	Estimate the average number or cost of repairs per unit during warranty or some time period.
-:•	Compare two or more sets of data from different designs, production periods, maintenance policies, environments, operating conditions, etc.
-:•	Predict future numbers and costs of repairs, such as, the next month, quarter, or year.
-:•	Reveal unexpected information and insight.
-{{mean cumulative function for recurrence data}}
-{{confidence limits for the MCF}}