I have data on two events over a 25-year expectations of time. The data look like (example below):

I"ve read about cross-correlation in this various other post, but I"ve never ever done time-series analysis before. Concerning the data:

I"d choose to view if Event_1 and also Event_2 over time.

You are watching: Event 1 and event 2 are correlated when

I suspect that Event_1 might cause Event_2, however it"s simply a guess: v (it could well it is in the opposite).

Any reference to the literature to get me started with this will be very appreciated.


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edited Nov 4 "17 in ~ 10:30
Enoch R.
inquiry Oct 31 "17 at 17:04
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Seems like a regression trouble with year.

Event_1 = Event_2 + Year + Event_2*Year

Well I thought I would expand on this a little more with the comment below.

You care around looking at the correlation in between two occasions with auto-correlation as an issue. Because that example, event 1 and event 2 could increase, yet that might be since they are correlated and also it can be because of auto-correlation.

The trick is to regulate for this within a model.

You can do something like a basic trend version as well: yt−yt−1=f(xt)+ error. Whereby yt-yt-1 is just the year to year change. F(xt) is the trend for x and also then you have error. Same thing as I defined with a tiny difference in notation.

There is one other thing you deserve to do: a logarithmic model. You will then obtain an idea if they space proportionately changing.


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edited Nov 1 "17 in ~ 0:42
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