Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with time-series
Search options not deleted
user 3591
Time series are data observed over time (either in continuous time or at discrete time periods).
1
vote
Time series with multiple subjects and multiple variables
As I mentioned in my note above, I would treat this as a regression problem. Here is a link to constructing, in R, the lag (and lead) variables from your data (R Head).
Included in the post is a brie …
- 916
0
votes
Identifying the time lag between cause and effect
I realize that this is probably a bit late, but one approach involves the use of a 1-dimensional version of Ripley's K-function. See, for example the paper by Doss or the nice introduction (and softw …
- 916