A small example data set that illustrates your question will be of great value 
to those trying to help. This appears to be a transformation that you are 
wanting to do (timestamp to units of time) so a data representing what you have 
(dput() is handy for this) and one representing what you want to have with any 
guidance regarding how to use the other columns in you data set (e.g., the 
event(0/1)).

Mark
R. Mark Sharp, Ph.D.
msh...@txbiomed.org





> On Jul 4, 2017, at 7:02 AM, Sunny Singha <sunnysingha.analyt...@gmail.com> 
> wrote:
>
> 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
>>>
>>> ______________________________________________
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>>> 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
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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