Consider the problem where I need to predict when a particular event is going to occur based on the past data (data available with time stamp) available.
For example
Assume a particular machine is running and we have the data collected from that particular machine and other similar kind of machine on various time stamps. The data include values collected from a machine which has failed on some functionality and also which is working properly.
What I need to do is to predict WHEN the particular machine(or some functionality) is going to fail.
From the problem What i understood is it is a time series analysis problem. I have heard about survival analysis where outcome is time. But I am not sure which other models I can try.
Could someone please explain which all models can be used for the particular problem (Assume i will be comparing the various quality matrices for models). I there are any approaches other than time series, please advise (My assumption is survival analysis is part of Time series analysis)
Technology to be used will be R or Python (scikit-learn)
Thanks in advance
Survival Analysis has been selected for the above problem as it provides the time when a particular event will occur. In the approach various models are under consideration and currently using coxph which we deem as the best model.