For this example we create a small data set that has a Poisson distribution
To run bootstrap, in each iteration we draw (with replacement) 100 numbers and compute standard WaveStats on the drawn sample.
The results for five iterations are shown in the table:
numPoints | 100 | 100 | 100 | 100 | 100 |
avg | 35.09 | 35.23 | 34.95 | 35.28 | 35.61 |
sdev | 2.19317 | 2.19667 | 2.20365 | 1.85363 | 2.14568 |
rms | 35.1578 | 35.2977 | 35.0187 | 35.3282 | 35.6739 |
adev | 1.83 | 1.8116 | 1.832 | 1.5144 | 1.6914 |
skew | -0.306796 | -0.171549 | 0.107583 | -0.276227 | -0.483667 |
kurt | -0.637302 | -0.595613 | -0.468839 | -0.173923 | -0.162058 |
sum | 3509 | 3523 | 3495 | 3528 | 3561 |
meanL1 | 34.6548 | 34.7941 | 34.5127 | 34.9122 | 35.1843 |
meanL2 | 35.5252 | 35.6659 | 35.3873 | 35.6478 | 36.0357 |
Increasing the number of samples does not change the results substantially:
The results for five iterations are shown in the table:
numPoints | 10000 | 10000 | 10000 | 10000 | 10000 |
avg | 35.2169 | 35.2089 | 35.2312 | 35.1799 | 35.2257 |
sdev | 2.04217 | 2.05121 | 2.06934 | 2.05897 | 2.04572 |
rms | 35.2761 | 35.2686 | 35.2919 | 35.2401 | 35.285 |
adev | 1.70327 | 1.71884 | 1.72827 | 1.71993 | 1.71226 |
skew | -0.212116 | -0.199756 | -0.192836 | -0.177744 | -0.215313 |
kurt | -0.424137 | -0.473013 | -0.439945 | -0.458874 | -0.450679 |
sum | 352169 | 352089 | 352312 | 351799 | 352257 |
meanL1 | 35.1769 | 35.1687 | 35.1906 | 35.1395 | 35.1856 |
meanL2 | 35.2569 | 35.2491 | 35.2718 | 35.2203 | 35.2658 |
Jacknife Example
We can use the Jacknife test to analyze the standard deviation of the same data. For this application our user function can be written in the form:
Wave inWave
WaveStats/Q inWave
return V_sdev
End
To run the Jacknife test execute:
The results are displayed in the table:
N | 50 |
stdEstimate | 1.72 |
JKEstimate | 1.71928 |
JKTEstimate | 1.7551 |
sigmaJKEstimate | 0.165026 |
It is interesting to observe the differences between the standard deviation obtained by the bootstrap approach (above) to the oen obtained here.
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