Thanks Boris and Bret, I was successful in simulating granular/transactional data. Now I need some guidance to transform the same data in format acceptable for survival analysis i.e below format:
pump_id | event_episode_no. | event(0/1) | start | stop | time_to_dropout The challenge I'm experience is to generate the 'start' and 'stop' in units of minutes/days from single column of 'Timestamp' which is the column from transactional/granular data based on condition tagged in separate column, 'event 0/1, (i.e event ). Please guide how to do such transformation in 'R'. Regards, Sandeep On Wed, Jun 28, 2017 at 2:51 PM, Boris Steipe <boris.ste...@utoronto.ca> wrote: > In principle what you need to do is the following: > > - break down the time you wish to simulate into intervals. > - for each interval, and each failure mode, determine the probability of > an event. > Determining the probability is the fun part, where you make your domain > knowledge explicit and include all the factors into your model: > cumulative load, > failure history, pressure, temperature, phase of the moon ... > - once you have a probability of failure, use the runif() function to > give you > a uniformly distributed random number in [0, 1]. If the number is > smaller than > your failure probability, accept the failure event, and record it. > - Repeat many times. > > Hope this helps. > B. > > > > > > On Jun 27, 2017, at 10:58 AM, sandeep Rana <sandyk...@gmail.com> wrote: > > > > Hi friends, > > I haven't done such a simulation before and any help would be greatly > appreciated. I need your guidance. > > > > I need to simulate end to end data for Reliability/survival analysis of > a Pump ,with correlation in place, that is at 'Transactional level' or at > the granularity of time-minutes, where each observation is a reading > captured via Pump's sensors each minute. > > Once transactional data is prepared I Then need to summarise above data > for reliability/ survival analysis. > > > > To begin with below is the transactional data format that i want prepare: > > Pump-id| Timestamp | temp | vibration | suction pressure| discharge > pressure | Flow > > > > Above transactional data has to be prepared with below failure modes > > Defects : > > (1) Cavitation – very high in frequency but low impact > > (2) Bearing Damage – very low in frequency but high impact > > (3) Worn Shaft – medium frequency but medium impact > > > > I have used survsim package but that's not what I need here. > > Please help and guide. > > > > Regards, > > Sandeep > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.