Table 2 Simulation results on structured measurement matrices with \(p = 2000\), \(n = 300\), \(\sigma ^{2} = 1\), \(s_0=40\), and \(r = 2300, 305\).

From: An adaptive shortest-solution guided decimation approach to sparse high-dimensional linear regression

r

Methods

TP

FP

RE

Time

2300

LASSO

40 (0)

32 (9.53)

4.05E−02 (3.59E−03)

9.40 (2.05)

ALASSO

40 (0)

32 (9.50)

4.03E−02 (3.17E−03)

12.66 (2.67)

VAMP

40 (0)

0 (0)

1.69E-03 (2.06E-04)

0.09 (0.05)

SIS+LASSO

22 (2.10)

26 (3.47)

7.02E−01 (5.16E−02)

0.80 (0.05)

ASDAR

40 (0)

0 (0)

1.69E−03 (2.06E−04)

0.13 (0.03)

ASSD

40 (0)

0 (0)

1.69E−03 (2.04E−04)

15.76 (2.67)

305

LASSO

40 (0)

101 (19.64)

9.41E−02 (2.43E−02)

30.38 (15.04)

ALASSO

40 (0)

100 (19.47)

9.31E−02 (2.28E−02)

44.84 (22.98)

VAMP

40 (0)

0 (0)

4.98E−03 (6.40E−04)

0.08 (0.05)

SIS+LASSO

14 (2.36)

30 (3.88)

8.70E−01 (4.43E−02)

0.99 (0.07)

ASDAR

38 (5.26)

30 (41.50)

1.25E−01 (3.06E−01)

0.37 (0.26)

ASSD

40 (0)

0 (0)

4.99E−03 (6.36E−04)

17.22 (7.06)

  1. Significant values are in bold.