Detecting the onset of unusual activity is the subject of outlier detection and nearly about every answer that i have recently made. A model reflecting period to period dependency and/or day-to=day dependency can be developed using Transfer Function/Dynamic Regression while "unusual" innovation can be detected when typical rules fail. If you wish to post your data I would be happy to take a look at it and hopefully other readers would do the same. Following is a very good thread with respect to anomaly (intervention) detection.http://stats.stackexchange.com/questions/104882/detecting-outliers-in-time-series-ls-ao-tc-using-tsoutliers-package-in-r-how . Read all the answers and comments and particularly closely follow the Tsay 1986 article http://www.unc.edu/~jbhill/tsay.pdf

Detecting the onset of unusual activity is the subject of outlier detection and nearly about every answer that i have recently made. A model reflecting period to period dependency and/or day-to=day dependency can be developed using Transfer Function/Dynamic Regression while "unusual" innovation can be detected when typical rules fail. If you wish to post your data I would be happy to take a look at it and hopefully other readers would do the same. Following is a very good thread with respect to anomaly (intervention) detection.https://stats.stackexchange.com/questions/104882/detecting-outliers-in-time-series-ls-ao-tc-using-tsoutliers-package-in-r-how . Read all the answers and comments and particularly closely follow the Tsay 1986 article http://www.unc.edu/~jbhill/tsay.pdf

Detecting the onset of unusual activity is the subject of outlier detection and nearly about every answer that i have recently made. A model reflecting period to period dependency and/or day-to=day dependency can be developed using Transfer Function/Dynamic Regression while "unusual" innovation can be detected when typical rules fail. outlier detection may also be of help.If you wish to post your data I would be happy to take a look at it and hopefully other readers would do the same.

Detecting the onset of unusual activity is the subject of outlier detection and nearly about every answer that i have recently made. A model reflecting period to period dependency and/or day-to=day dependency can be developed using Transfer Function/Dynamic Regression while "unusual" innovation can be detected when typical rules fail. If you wish to post your data I would be happy to take a look at it and hopefully other readers would do the same. Following is a very good thread with respect to anomaly (intervention) detection.http://stats.stackexchange.com/questions/104882/detecting-outliers-in-time-series-ls-ao-tc-using-tsoutliers-package-in-r-how . Read all the answers and comments and particularly closely follow the Tsay 1986 article http://www.unc.edu/~jbhill/tsay.pdf