. 2015 Jun 20;31(20):3282–3289. doi: 10.1093/bioinformatics/btv378

Table 1.

Sampling efficiency in modeling simulated population trajectories

	Method	AP	s/iter	minESS(f)/s	spdup(f)	ESS(τ)/s	spdup(τ)
	ES²	1.00	1.62E-03	0.19	1.00	0.27	1.00
	MALA	0.77	1.06E-03	0.70	3.76	2.13	7.86
I	aMALA	0.64	7.73E-03	0.14	0.73	0.10	0.37
	HMC	0.75	9.39E-03	1.88	10.08	1.77	6.52
	splitHMC	0.72	6.71E-03	2.64	14.17	2.71	10.02
	ES²	1.00	1.68E-03	0.22	1.00	0.28	1.00
	MALA	0.76	1.05E-03	0.55	2.53	2.11	7.40
II	aMALA	0.66	8.00E-03	0.06	0.29	0.12	0.41
	HMC	0.73	1.23E-02	2.94	13.47	1.34	4.69
	splitHMC	0.75	7.12E-03	5.22	23.93	2.73	9.58
	ES²	1.00	1.67E-03	0.21	1.00	0.33	1.00
	MALA	0.75	1.12E-03	0.55	2.66	1.91	5.81
III	aMALA	0.65	8.11E-03	0.07	0.34	0.10	0.31
	HMC	0.75	1.27E-02	2.23	10.68	1.05	3.20
	splitHMC	0.75	7.66E-03	3.78	18.09	2.04	6.23
	ES²	1.00	1.66E-03	0.25	1.00	0.14	1.00
	MALA	0.83	1.11E-03	0.51	2.05	1.69	12.18
IV	aMALA	0.65	8.18E-03	0.07	0.30	0.08	0.60
	HMC	0.81	1.17E-02	0.58	2.30	0.87	6.25
	splitHMC	0.76	7.78E-03	0.80	3.21	1.38	9.96

The true population trajectories are (I) logistic, (II) exponential growth, (III) boombust and (IV) bottleneck. AP, acceptance probability; s/iter, seconds per sampling iteration; ‘spdup’, speedup of efficiency measurement minESS/s using ES² as baseline.