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Book Categories |
1.0 | Introduction | 1 |
2.0 | The bootstrap principle | 11 |
2.1 | The principle of resampling | 11 |
2.2 | The principle of pivoting and variance stabilisation | 49 |
2.3 | Limitations of the bootstrap | 57 |
2.4 | Trends in bootstrap resampling | 59 |
2.5 | Summary | 60 |
3.0 | Signal detection with the bootstrap | 62 |
3.1 | Principles of hypothesis testing | 62 |
3.2 | Hypothesis testing with the bootstrap | 73 |
3.3 | The role of pivoting | 74 |
3.4 | Variance estimation | 78 |
3.5 | Detection through regression | 83 |
3.6 | The bootstrap matched filter | 93 |
3.7 | Summary | 101 |
4.0 | Bootstrap model selection | 103 |
4.1 | Preliminaries | 103 |
4.2 | Model selection | 105 |
4.3 | Model selection in linear models | 106 |
4.4 | Model selection in nonlinear models | 114 |
4.5 | Order selection in autoregressions | 117 |
4.6 | Detection of sources using bootstrap techniques | 119 |
4.7 | Summary | 127 |
5.0 | Real data bootstrap applications | 130 |
5.1 | Optimal sensor placement for knock detection | 130 |
5.2 | Confidence intervals for aircraft parameters | 136 |
5.3 | Landmine detection | 143 |
5.4 | Noise floor estimation in over-the-horizon radar | 147 |
5.5 | Model order selection for corneal elevation | 154 |
5.6 | Summary | 158 |
App. 1 | Matlab codes for the examples | 159 |
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