An example of using the `jackknife' and `bootstrap' estimation: Finding bias-corrected estimates and confidence intervals for the true standard deviation from a sample. The starting random-number seed is 23456 A sample of 30 standard normal R.V.s is: -0.8720 0.1020 0.0895 -0.3867 -0.2771 1.4472 0.1625 0.5456 1.7043 0.3594 0.0773 -0.8783 0.3176 -0.3142 -1.6018 0.7049 1.0378 1.2692 -1.0916 1.6173 -0.0572 -1.4082 0.7606 -0.0179 0.1951 0.6653 -0.6595 0.2604 -0.4153 1.6192 A sample of 30 normal variables with mean=3 and st.dev.=5 is 4.775 5.059 8.711 -1.764 8.123 3.321 3.286 9.796 6.324 -8.932 -0.061 0.058 -2.141 0.997 -1.786 -1.282 7.753 14.489 1.595 5.068 8.989 8.860 13.986 8.685 4.464 1.951 -0.106 10.779 3.735 0.561 OBSERVED sample mean: 4.1763 Sample standard deviation: 5.2550 CLASSICAL NORMAL-THEORY CONFIDENCE INTERVAL: The 0.025, 0.500, and 0.975 quantiles of ChiSquare(29) are 16.0471 28.3361 45.7223 The classical symmetric 95% CI for sdev is ( 4.1852, 7.0644) (This is an exact CI, but assumes normal variables. It is based on quantiles of the chi-square distribution with df=29 degrees of freedom.) JACKKNIFE CONFIDENCE INTERVALS: For the jackknife of sdev itself: Est Sdev=5.2550: The sdev delete-1 jackknife values are: 5.347 5.345 5.277 5.225 5.294 5.346 5.345 5.238 5.332 4.717 5.286 5.289 5.208 5.313 5.224 5.244 5.304 4.967 5.325 5.345 5.267 5.272 5.005 5.277 5.348 5.331 5.284 5.195 5.347 5.303 The sdev jackknife pseudo-values are: 2.593 2.636 4.631 6.134 4.126 2.631 2.637 5.754 3.020 20.849 4.367 4.266 6.608 3.573 6.160 5.572 3.844 13.603 3.226 2.637 4.895 4.771 12.516 4.607 2.566 3.054 4.405 6.987 2.577 3.872 The mean and sample sdev of the 30 pseudovalues are: 5.30392 3.9253 The pseudovalue 95% symmetric CI for sdev is ( 3.8993, 6.7086) Using Student-t (df=29) 95% CI instead: ( 3.8382, 6.7697) For the jackknife of log(sdev): Log(sdev)=0.0000: The 30 logsdev delete-1 jackknife values are: 1.677 1.676 1.663 1.653 1.667 1.676 1.676 1.656 1.674 1.551 1.665 1.666 1.650 1.670 1.653 1.657 1.668 1.603 1.672 1.676 1.662 1.662 1.610 1.663 1.677 1.674 1.665 1.648 1.677 1.668 The log(sdev) jackknife pseudo-values are: 1.157 1.165 1.541 1.827 1.445 1.164 1.165 1.754 1.237 4.790 1.491 1.472 1.918 1.341 1.832 1.720 1.392 3.293 1.276 1.165 1.591 1.567 3.075 1.536 1.152 1.243 1.498 1.991 1.154 1.397 The mean and sample sdev of the 30 log pseudovalues are: 1.67824 0.773893 The pseudovalue 95% symmetric CI for logsdev is ( 1.4013, 1.9552) The exponentiated mean and exponentiated 95% symmetric CI are 5.3561 ( 4.0605, 7.0652) Using Student-t (df=29) exponentiated 95% CI instead: ( 4.0119, 7.1507) BOOTSTRAP CONFIDENCE INTERVAL: Doing 1000 bootstrap replications for the sample standard deviation: Sorting the 1000 bootstrap replications: The first 30 sorted bootstrap sdev values are (#1-#30): 3.160 3.212 3.223 3.288 3.363 3.510 3.529 3.537 3.544 3.546 3.565 3.566 3.634 3.646 3.662 3.681 3.744 3.762 3.800 3.816 3.826 3.839 3.853 3.862 3.865 3.870 3.872 3.886 3.894 3.905 The last 30 sorted bootstrap sdev values are (#971-#1000): 6.350 6.352 6.361 6.377 6.402 6.412 6.472 6.478 6.508 6.516 6.517 6.532 6.557 6.579 6.592 6.594 6.619 6.621 6.636 6.674 6.680 6.707 6.788 6.873 6.888 6.921 6.982 7.043 7.138 7.167 Bootstrap median bias (sdev=5.25505): 566/1000 = 0.566 Bootstrap median: 5.1333 95% Percentile CI: ( 3.8647, 6.4117) SUMMARY (Estimator of sdev, 95% symmetric CI for sdev): NormalTheory 5.3162 ( 4.1852, 7.0644) Sdev Jackknife 5.3039 ( 3.8993, 6.7086) LogSdev Jackknife 5.3561 ( 4.0605, 7.0652) Bootstrap 5.1333 ( 3.8647, 6.4117) Student-t CIs: Sdev Jackknife 5.3039 ( 3.8382, 6.7697) LogSdev Jackknife 5.3561 ( 4.0119, 7.1507) Sample size: 30 Number of bootstrap replications: 1000 Starting random-number seed: 23456 The `Sdev Jackknife' CI seems to track the exact CI best, even for different starting seeds and different numbers of bootstrap replication. Random numbers used: 30,070