Table 6
“Limited-memory” “data-space” algorithm results.
Dataset | Cost | Penalty |
![]() |
Total number |
function | (β/β0) | (d.o.f.) | of “time bins” | |
|
||||
V0332+53 | C.9 | 0 | 1.062( 6595) | 97 |
C.8 | 1 | 1.059( 6592) | 100 | |
C.8 | 0.32 | 0.995( 6492) | 200 | |
C.8 | 0.05 | 0.997( 16 533) | 2147 | |
GX 339-4 | C.9 | 0 | 1.202( 19 930) | 940 |
C.9 | 0.02 | 1.197( 19 906) | 964 | |
C.8 | 1 | 1.278( 20 108) | 762 | |
C.8 | 0.2 | 1.030( 18 951) | 1919 | |
GRS 1915+105 | C.9 | 0 | 1.241( 51 553) | 424 |
C.9 | 0.02 | 1.237( 51 565) | 412 | |
C.8 | 1 | 1.246( 51 585) | 392 | |
C.8 | 0.2 | 1.215( 51 023) | 954 | |
Cyg X-1 | C.9 | 0 | 1.436( 40 068) | 676 |
C.8 | 1 | 1.475( 40 120) | 624 | |
C.8 | 0.02 | 1.292( 38 948) | 1796 |
Notes.The “limited” version is parameterized as indicated in Sect. 6.3.4. The penalty parameter is measured in units of β0 = log (M), where M is the number of data points of the dataset. The bold penalty parameters used throughout the analysis are indicated in bold. C.8 indicates that the cost function is the chi-square and C.9 the cost function obtained with a “flat-prior” hypothesis.
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