Table 2. Model parameters (median), absolute WAIC and relative.

ΔWAIC values for the three candidate models in the four sequences of visual noise.

Sequence	Model	σA	Pcommon	σ0	${\displaystyle \kappa }$ or γ	WAIC	ΔWAIC
Sinusoid	Instantaneous learner	5.56	0.63	8.95	-	81931.2	109.9
	Bayesian learner	5.64	0.65	9.03	κ: 7.37	81821.3	0
	Exponential discounting	5.62	0.64	9.02	γ: 0.23	81866.9	45.6
RW1	Instantaneous learner	6.30	0.69	8.46	-	110051.2	89.0
	Bayesian learner	6.29	0.72	8.68	κ: 8.06	109962.2	0
	Exponential discounting	6.26	0.70	8.75	γ: 0.33	109929.9	−32.3
RW2	Instantaneous learner	6.36	0.72	10.79	-	62576.4	201.3
	Bayesian learner	6.49	0.78	10.9	κ: 6.7	62375.2	0
	Exponential discounting	6.46	0.73	11.0	γ: 0.25	62421.5	46.3
Sinusoid with intermittent jumps	Instantaneous learner	6.38	0.65	8.19	-	83891.4	94.9
	Bayesian learner	6.45	0.68	8.26	κ: 6.13	83796.5	0
	Exponential discounting	6.43	0.67	8.20	γ: 0.24	83798.1	1.64

Note: WAIC values were computed for each participant and summed across participants. A low WAIC indicates a better model. ΔWAIC is relative to the WAIC of the Bayesian learner.