A Fast Screen and Shape Recognition Algorithm for Multiple Change-Point Detection

Table 2

Distribution of for the various competing methods and sample sizes (100 simulated sample paths) with BIC values and run times ( error case).

Sample Size		Method		-2	-1	0	1	2		BIC	Time
n=500	N=5	FSSR	23	21	27	20	8	0	1	0.3016	0.0266
		SaRa	9	11	37	21	18	2	2	0.4719	0.0233
		mSaRa	39	23	26	11	1	0	0	0.4054	0.2920
n=3000	N=10	FSSR	18	32	19	24	5	0	2	1.6737	0.1009
		SaRa	37	9	5	12	3	12	22	2.7135	0.1253
		mSaRa	47	11	8	8	8	3	15	2.0120	0.6151
	N=15	FSSR	55	28	12	2	2	1	0	1.6977	0.1240
		SaRa	68	3	9	5	2	1	12	3.1348	0.1283
		mSaRa	80	6	6	3	4	1	0	2.1958	0.6368
n=5000	N=10	FSSR	18	19	30	20	11	2	0	2.7748	0.1771
		SaRa	35	8	6	5	5	4	37	4.3186	0.2001
		mSaRa	38	4	8	10	6	4	30	3.3002	0.8318
	N=20	FSSR	66	23	9	7	1	0	0	2.7637	0.1921
		SaRa	77	4	4	1	6	2	6	5.0548	0.1948
		mSaRa	91	2	4	0	2	0	1	3.5509	0.8705
	N=30	FSSR	99	1	0	0	0	0	0	2.8936	0.2050
		SaRa	90	0	4	1	0	2	3	6.3680	0.1879
		mSaRa	99	1	0	0	0	0	0	4.2754	0.8828
n=8000	N=10	FSSR	10	15	37	27	9	2	0	4.4204	0.2831
		SaRa	17	5	3	5	6	5	59	6.8527	0.3153
		mSaRa	15	7	6	4	4	9	55	4.9348	1.3940
	N=20	FSSR	30	30	28	10	2	0	0	4.3621	0.3262
		SaRa	61	5	5	4	4	5	16	8.6200	0.3047
		mSaRa	76	4	4	5	2	1	8	5.6735	1.2837
	N=30	FSSR	93	5	2	0	0	0	0	4.4635	0.3484
		SaRa	90	2	4	1	1	0	2	10.5598	0.3003
		mSaRa	95	2	0	0	2	0	1	6.6622	1.1897
	N=50	FSSR	100	0	0	0	0	0	0	4.7080	0.3608
		SaRa	98	1	0	1	0	0	0	12.0999	0.3109
		mSaRa	100	0	0	0	0	0	0	7.3868	1.2347