Table 1: Results of numerical experiments comparing age determination methods using the step method, the corrected step method, the Monte Carlo method, and Bayesian estimation. Each line gives summary statistics from 1000 independent sets of synthetic data generated with the uncertainties specified in the first three columns. All ages are in Gyr. See Sect. 4.3 for further explanation.
Assumed $\sigma$ in Median $\tau_{\rm est}$ , $\pm$ median $\sigma_\tau$ , (% within CI), [median absolute deviation]

[Me/H] $\log T_{\rm eff}$ M_V Step method Corrected Monte Carlo Bayesian

Case 1: True age $\tau_{\rm true}=2.18$ Gyr

0.05 0.005 0.05 $2.19\pm 0.11$ (44%) [0.13] $\pm0.19$ (67%) $2.16\pm 0.20$ (71%) [0.13] $\rm 2.18^{+0.18}_{-0.20}$ (66%) [0.14]

0.10 0.010 0.10 $2.15\pm 0.24$ (42%) [0.27] $\pm0.41$ (73%) $2.12\pm 0.51$ (75%) [0.32] $\rm 2.20^{+0.36}_{-0.42}$ (68%) [0.25]

0.20 0.020 0.20 $2.05\pm 0.61$ (50%) [0.65] $\pm1.05$ (77%) $2.13\pm 1.01$ (70%) [0.68] $\rm 2.14^{+0.63}_{-0.88}$ (76%) [0.40]

Case 2: True age $\tau_{\rm true}=2.85$ Gyr

0.05 0.005 0.05 $2.98\pm 0.13$ (48%) [0.23] $\pm0.22$ (72%) $3.10\pm 0.49$ (68%) [0.27] $\rm 2.83^{+0.21}_{-0.14}$ (72%) [0.09]

0.10 0.010 0.10 $3.13\pm 0.44$ (41%) [0.46] $\pm0.76$ (64%) $3.17\pm 0.65$ (64%) [0.47] $\rm 2.76^{+0.36}_{-0.27}$ (71%) [0.21]

0.20 0.020 0.20 $3.05\pm 0.66$ (44%) [0.69] $\pm1.14$ (70%) $3.21\pm 1.10$ (69%) [0.70] $\rm 2.60^{+0.61}_{-0.52}$ (70%) [0.37]

**Table 1:** Results of numerical experiments comparing age determination methods using the step method, the corrected step method, the Monte Carlo method, and Bayesian estimation. Each line gives summary statistics from 1000 independent sets of synthetic data generated with the uncertainties specified in the first three columns. All ages are in Gyr. See Sect. 4.3 for further explanation.
Assumed $\sigma$ in		Median $\tau_{\rm est}$ , $\pm$ median $\sigma_\tau$ , (% within CI), [median absolute deviation]

[Me/H]	$\log T_{\rm eff}$	M_V	Step method	Corrected	Monte Carlo	Bayesian
Case 1: True age $\tau_{\rm true}=2.18$ Gyr
0.05	0.005	0.05	$2.19\pm 0.11$ (44%) [0.13]	$\pm0.19$ (67%)	$2.16\pm 0.20$ (71%) [0.13]	$\rm 2.18^{+0.18}_{-0.20}$ (66%) [0.14]
0.10	0.010	0.10	$2.15\pm 0.24$ (42%) [0.27]	$\pm0.41$ (73%)	$2.12\pm 0.51$ (75%) [0.32]	$\rm 2.20^{+0.36}_{-0.42}$ (68%) [0.25]
0.20	0.020	0.20	$2.05\pm 0.61$ (50%) [0.65]	$\pm1.05$ (77%)	$2.13\pm 1.01$ (70%) [0.68]	$\rm 2.14^{+0.63}_{-0.88}$ (76%) [0.40]
Case 2: True age $\tau_{\rm true}=2.85$ Gyr
0.05	0.005	0.05	$2.98\pm 0.13$ (48%) [0.23]	$\pm0.22$ (72%)	$3.10\pm 0.49$ (68%) [0.27]	$\rm 2.83^{+0.21}_{-0.14}$ (72%) [0.09]
0.10	0.010	0.10	$3.13\pm 0.44$ (41%) [0.46]	$\pm0.76$ (64%)	$3.17\pm 0.65$ (64%) [0.47]	$\rm 2.76^{+0.36}_{-0.27}$ (71%) [0.21]
0.20	0.020	0.20	$3.05\pm 0.66$ (44%) [0.69]	$\pm1.14$ (70%)	$3.21\pm 1.10$ (69%) [0.70]	$\rm 2.60^{+0.61}_{-0.52}$ (70%) [0.37]

Source LaTeX | All tables | In the text

	1 Introduction
	2 Problem formulation and assumptions
	3 Bayesian estimation of stellar ages
	4 Comparison with age estimates from conventional isochrone fitting
	5 Application of the Bayesian age estimator
	6 Discussion
	7 Conclusions
	References