Benchmark Report [Results .csv]

Configuration

Length of signals: 512

Repetitions: 2000

SNRin values: -5, 0, 5, 10,

Methods

• monte_carlo_test

• global_mad_test

• global_rank_env_test

• APF

Signals

• LinearChirp

Mean results tables:

The results shown here are the average and 95% Clopper-Pearson CI of the estimated detection power with Bonferroni correction. Best performances are bolded.

Signal: LinearChirp [View Plot] [Get .csv]

	Method + Param	SNRin=-5dB (average)	SNRin=-5dB (CI)	SNRin=0dB (average)	SNRin=0dB (CI)	SNRin=5dB (average)	SNRin=5dB (CI)	SNRin=10dB (average)	SNRin=10dB (CI)
0	monte_carlo_test{‘statistic’: ‘Frs’, ‘pnorm’: 2, ‘rmax’: 1.0, ‘MC_reps’: 199}	0.08	[‘0.06’, ‘0.10’]	0.23	[‘0.20’, ‘0.26’]	0.80	[‘0.78’, ‘0.83’]	1.00	[‘1.00’, ‘1.00’]
1	monte_carlo_test{‘statistic’: ‘Frs_vs’, ‘pnorm’: 2, ‘rmax’: 1.0, ‘MC_reps’: 199}	0.09	[‘0.07’, ‘0.11’]	0.42	[‘0.39’, ‘0.45’]	0.99	[‘0.99’, ‘1.00’]	1.00	[‘1.00’, ‘1.00’]
2	global_mad_test{‘statistic’: ‘Frs’, ‘MC_reps’: 199}	0.07	[‘0.06’, ‘0.09’]	0.23	[‘0.20’, ‘0.25’]	0.78	[‘0.75’, ‘0.80’]	1.00	[‘1.00’, ‘1.00’]
3	global_mad_test{‘statistic’: ‘Frs_vs’, ‘MC_reps’: 199}	0.08	[‘0.07’, ‘0.10’]	0.42	[‘0.39’, ‘0.45’]	1.00	[‘0.99’, ‘1.00’]	1.00	[‘1.00’, ‘1.00’]
4	global_rank_env_test{‘fun’: ‘Fest’, ‘correction’: ‘rs’}	0.08	[‘0.06’, ‘0.10’]	0.31	[‘0.29’, ‘0.34’]	0.99	[‘0.98’, ‘1.00’]	1.00	[‘1.00’, ‘1.00’]
5	global_rank_env_test{‘fun’: ‘Fest’, ‘correction’: ‘rs’, ‘rmin’: 0.65, ‘rmax’: 1.05}	0.11	[‘0.09’, ‘0.13’]	0.49	[‘0.46’, ‘0.52’]	1.00	[‘0.99’, ‘1.00’]	1.00	[‘1.00’, ‘1.00’]
6	global_rank_env_test{‘fun’: ‘Fest’, ‘correction’: ‘rs’, ‘transform’: ‘asin(sqrt(.))’}	0.07	[‘0.06’, ‘0.09’]	0.31	[‘0.28’, ‘0.34’]	0.99	[‘0.99’, ‘1.00’]	1.00	[‘1.00’, ‘1.00’]
7	global_rank_env_test{‘fun’: ‘Fest’, ‘correction’: ‘rs’, ‘rmin’: 0.65, ‘rmax’: 1.05, ‘transform’: ‘asin(sqrt(.))’}	0.11	[‘0.10’, ‘0.14’]	0.49	[‘0.46’, ‘0.52’]	1.00	[‘0.99’, ‘1.00’]	1.00	[‘1.00’, ‘1.00’]
8	APF	0.11	[‘0.09’, ‘0.13’]	0.29	[‘0.26’, ‘0.32’]	0.51	[‘0.48’, ‘0.55’]	0.70	[‘0.67’, ‘0.73’]