Table S1.

Coverage rates for 95% nominal confidence intervals obtained by cross-validated cross-estimation with the joint lasso procedure, Eq. 23

				p
				60		500
				n
Signal	Noise	Correlation	Design	80	200	80	200
Dense	$\sigma =0.1$	$\rho =0$	Gauss. X	0.94	0.96	0.95	0.95
	$\sigma =0.1$	$\rho =0$	Bern. X	0.95	0.95	0.94	0.95
	$\sigma =0.1$	$\rho =0.9$	Gauss. X	0.94	0.94	0.94	0.95
	$\sigma =0.1$	$\rho =0.9$	Bern. X	0.93	0.95	0.93	0.92
	$\sigma =1$	$\rho =0$	Gauss. X	0.95	0.95	0.92	0.94
	$\sigma =1$	$\rho =0$	Bern. X	0.93	0.95	0.94	0.93
	$\sigma =1$	$\rho =0.9$	Gauss. X	0.93	0.94	0.93	0.94
	$\sigma =1$	$\rho =0.9$	Bern. X	0.95	0.96	0.92	0.94
Geometric	$\sigma =0.1$	$\rho =0$	Gauss. X	0.94	0.95	0.93	0.94
	$\sigma =0.1$	$\rho =0$	Bern. X	0.92	0.95	0.94	0.96
	$\sigma =0.1$	$\rho =0.9$	Gauss. X	0.95	0.94	0.95	0.95
	$\sigma =0.1$	$\rho =0.9$	Bern. X	0.94	0.93	0.95	0.94
	$\sigma =1$	$\rho =0$	Gauss. X	0.94	0.94	0.94	0.94
	$\sigma =1$	$\rho =0$	Bern. X	0.95	0.94	0.95	0.95
	$\sigma =1$	$\rho =0.9$	Gauss. X	0.91	0.96	0.94	0.95
	$\sigma =1$	$\rho =0.9$	Bern. X	0.95	0.97	0.94	0.95
Sparse	$\sigma =0.1$	$\rho =0$	Gauss. X	0.94	0.96	0.94	0.95
	$\sigma =0.1$	$\rho =0$	Bern. X	0.95	0.95	0.92	0.94
	$\sigma =0.1$	$\rho =0.9$	Gauss. X	0.92	0.95	0.93	0.96
	$\sigma =0.1$	$\rho =0.9$	Bern. X	0.93	0.95	0.92	0.97
	$\sigma =1$	$\rho =0$	Gauss. X	0.94	0.93	0.94	0.95
	$\sigma =1$	$\rho =0$	Bern. X	0.94	0.93	0.93	0.95
	$\sigma =1$	$\rho =0.9$	Gauss. X	0.95	0.94	0.93	0.95
	$\sigma =1$	$\rho =0.9$	Bern. X	0.94	0.94	0.94	0.94

All numbers are aggregated over 500 simulation runs; the above numbers thus have a standard sampling error of roughly 0.01. Bern., Bernoulli; Gauss., Gaussian.