Table 1.
Distributions of glitch sizes: results of fits and AIC weights for each model; using glitches with Δν ≥ 0.01 μHz.
| PSR name | wGauss | wPower law | wL-N | wExp |  |
 |
 |
 |
 |
 |
|---|---|---|---|---|---|---|---|---|---|---|
| μHz | μHz | (μHz)−1 | ||||||||
| J0205+6449 | 10−8 | 0.66 | 0.33 | 10−5 | 15(5) | 20(4) | 1.27(6) | 0.7(7) | 2.5(3) | 0.07(6) |
| B0531+21 | 10−17 | 0.02 | 0.97 | 10−7 | 1.2(5) | 3(1) | 1.4(1) | −1.3(3) | 1.5(2) | 0.8(7) |
| J0537−6910 | 0.96 | 10−24 | 10−8 | 0.03 | 15(1) | 9.9(9) | 1.19(5) | 2.2(2) | 1.3(2) | 0.063(6) |
| J0631+1036 | 10−12 | 0.94 | 0.05 | 10−8 | 1(1) | 3(1) | 1.4(1) | −1.9(6) | 2.1(4) | 0.61(4) |
| B0833−45 | 0.997 | 10−13 | 10−6 | 0.002 | 21(2) | 9(1) | 1.2(4) | 2.7(2) | 1.2(4) | 0.05(1) |
| B1338−62 | 10−5 | 0.07 | 0.53 | 0.4 | 2.5(5) | 2.7(3) | 1.36(5) | −0.1(3) | 1.6(1) | 0.4(1) |
| B1737−30 | 10−14 | 0.82 | 0.17 | 10−7 | 0.6(2) | 1.0(2) | 1.38(6) | −2.0(3) | 1.9(1) | 1.5(8) |
| B1758−23 | 0.06 | 0.004 | 0.07 | 0.866 | 0.6(1) | 0.51(8) | 1.3(2) | −1.2(4) | 1.5(3) | 1.7(6) |
Notes. wm denotes the Akaike weight of the model m. 
and 
are the mean and the standard deviation of the Gaussian model, and 
is the power-law index. 
and 
are the mean and the standard deviation of the log-normal model, respectively. 
is the rate parameter of the exponential distribution. The values in parentheses correspond to the uncertainty in the last quoted digit and were calculated using the usual bootstrap method. We marked in bold the values of wm for the best models.
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