Skip to Main Content
Table 5.

Changepoint detection and model identification results (%) for 1000 sets of five target–neighbor difference ({Dt}) series (n = 100). Parameters were added as indicated to the target series and c = 50 for the target simulated under M3, M4, and M5. The neighbor series always followed M1 (constant mean with no breaks). CRC refers to the pairwise algorithm’s detection results for the target series. The percentage of {Dt} identified correctly is given in bold.

Changepoint detection and model identification results (%) for 1000 sets of five target–neighbor difference ({Dt}) series (n = 100). Parameters were added as indicated to the target series and c = 50 for the target simulated under M3, M4, and M5. The neighbor series always followed M1 (constant mean with no breaks). CRC refers to the pairwise algorithm’s detection results for the target series. The percentage of {Dt} identified correctly is given in bold.
Changepoint detection and model identification results (%) for 1000 sets of five target–neighbor difference ({Dt}) series (n = 100). Parameters were added as indicated to the target series and c = 50 for the target simulated under M3, M4, and M5. The neighbor series always followed M1 (constant mean with no breaks). CRC refers to the pairwise algorithm’s detection results for the target series. The percentage of {Dt} identified correctly is given in bold.
Close Modal

or Create an Account

Close Modal
Close Modal