Hi! I have some data obatained from some real-time measurements for some period of time per snapshot basis. After some post-processing of the data, I am able to extract the following information:
1)Number of paths as per time snapshot 2)Number of NEW paths as per time snapshot 3)Number of DEATH paths as per time snapshot 4)Lifespan of each path during the whole measurement run My aim now is to model this information so by some stochastic process so that the above information can be regenerated via computer simulation. I came across some related arcticles that discuss about Birth-Death Process, Poisson Process and Markov Proccess. I have look into some books to gain some theoretical backround on these topics. However, I am not entirely sure, how should I relate my measuement information to these processes. Morever, how do I know which processes will be more appropriate to my case? I hope to get some suggestions & ideas the direction I should look into to derive a stochastic model that appropriately model my data! Thanks so much. CCC . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
