Lets say you live in an apartment complex. In the past month, a number of
vehicles parked in the unsecured apartment complex have been broken into.
Items stolen included laptops, credit cards, purses, wallets, stereo
equipment etc.
Of those reported....some folks don't bother.....you have a list of the
dates and times that the victims discovered and reported the crime. Times may
or may not be accurate, because the victim might have been asleep and didn't
discover they were a victim until the next morning. The apartment residents
want some action and help to catch the criminal and you need to advise the
boss when would be a good time to send undercover officers to the area to
observe activities in the parking lot.
The dates and times are not necessarily evenly spaced.
Days vary from 1 to 5, 10,20 between incidents.
Times vary within the 24 hour clock.
However, you can see patterns in the data, i.e. the time may be between 1AM
and 5AM, sometimes earlier or later but the majority are in one time frame.
Days could be say always Wednesday or maybe Sunday and Thursday, or Tuesday,
Wednesday and Thursday.
There is a pattern there.
So all I'm trying to do is find the formula(s) that will give the best
probability of when the next incident will occur based on the days between
past events and the time of day that past events occured.
I know it can be done.....but not how to do it.
Rich
