Subsampling:
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York, N.Y. [u.a.]
Springer
1999
|
| Series: | Springer series in statistics
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Hier auch später erschienene, unveränderte Nachdrucke |
| Physical Description: | XV, 347 S. graph. Darst. |
| ISBN: | 0387988548 9781461271901 |
Staff View
MARC
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| 245 | 1 | 0 | |a Subsampling |c Dimitris N. Politis ; Joseph P. Romano ; Michael Wolf |
| 264 | 1 | |a New York, N.Y. [u.a.] |b Springer |c 1999 | |
| 300 | |a XV, 347 S. |b graph. Darst. | ||
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Record in the Search Index
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| adam_text |
Contents
Preface vii
I Basic Theory 1
1 Bootstrap Sampling Distributions 3
1.1 Introduction 3
1.1.1 Pivotal Method 4
1.1.2 Asymptotic Pivotal Method 6
1.1.3 Asymptotic Approximation 6
1.1.4 Bootstrap Approximation 7
1.2 Consistency 9
1.3 Case of the Nonparametric Mean 11
1.4 Generalizations to Mean like Statistics 16
1.5 Bootstrapping the Empirical Process 19
1.6 Differentiability and the Bootstrap 23
1.7 Further Examples 30
1.8 Hypothesis Testing 33
1.9 Conclusions 38
2 Subsampling in the I.I.D. Case 39
2.1 Introduction 39
2.2 The Basic Theorem 41
2.3 Comparison with the Bootstrap 47
2.4 Stochastic Approximation 51
xii Contents
2.5 General Parameters and Other Choices of Root 52
2.5.1 Studentized Roots 52
2.5.2 General Parameter Space 53
2.6 Hypothesis Testing 54
2.7 Data Dependent Choice of Block Size 59
2.8 Variance Estimation: The Delete d Jackknife 62
2.9 Conclusions 64
3 Subsampling for Stationary Time Series 65
3.1 Introduction 65
3.2 Univariate Parameter Case 67
3.2.1 Some Motivation: The Simplest Example 67
3.2.2 Theory and Methods for the General Univariate
Parameter Case 68
3.2.3 Studentized Roots 74
3.3 Multivariate Parameter Case 74
3.4 Examples 77
3.5 Hypothesis Testing 90
3.6 Data Dependent Choice of Block Size 92
3.7 Bias Reduction 93
3.8 Variance Estimation 95
3.8.1 General Statistic Case 95
3.8.2 Case of the Sample Mean 97
3.9 Comparison with the Moving Blocks Bootstrap 98
3.10 Conclusions 100
4 Subsampling for Nonstationary Time Series 101
4.1 Introduction 101
4.2 Univariate Parameter Case 102
4.3 Multivariate Parameter Case 106
4.4 Examples 108
4.5 Hypothesis Testing and Data Dependent Choice of Block
Size 117
4.6 Variance Estimation 117
4.7 Conclusions 119
5 Subsampling for Random Fields 120
5.1 Introduction and Definitions 120
5.2 Some Useful Notions of Strong Mixing for Random Fields . 121
5.3 Consistency of Subsampling for Random Fields 123
5.3.1 Univariate Parameter Case 123
5.3.2 Multivariate Parameter Case 127
5.4 Variance Estimation and Bias Reduction 129
5.5 Maximum Overlap Subsampling in Continuous Time . . . 132
5.6 Some Illustrative Examples 134
Contents xiii
5.7 Conclusions 137
6 Subsampling Marked Point Processes 138
6.1 Introduction 138
6.2 Definitions and Some Different Notions on Mixing . 140
6.3 Subsampling Stationary Marked Point Processes 144
6.3.1 Sampling Setup and Assumptions 144
6.3.2 Main Consistency Result 146
6.3.3 Nonstandard Asymptotics 149
6.4 Stochastic Approximation 151
6.5 Variance Estimation via Subsampling 154
6.6 Examples 155
6.7 Conclusions 158
7 Confidence Sets for General Parameters 159
7.1 Introduction 159
7.2 A Basic Theorem for the Empirical Measure 160
7.3 A General Theorem on Subsampling 164
7.4 Subsampling the Empirical Process 166
7.5 Subsampling the Spectral Measure 168
7.6 Conclusions 170
II Extensions, Practical Issues, and Applications 171
8 Subsampling with Unknown Convergence Rate 173
8.1 Introduction 173
8.2 Estimation of the Convergence Rate 177
8.2.1 Convergence Rate Estimation: Univariate
Parameter Case 177
8.2.2 Convergence Rate Estimation: Multivariate
Parameter Case 182
8.3 Subsampling with Estimated Convergence Rate 184
8.4 Conclusions 187
9 Choice of the Block Size 188
9.1 Introduction 188
9.2 Variance Estimation 189
9.2.1 Case of the Sample Mean 189
9.2.2 General Case 192
9.3 Estimation of a Distribution Function 193
9.3.1 Calibration Method 194
9.3.2 Minimum Volatility Method 197
9.4 Hypothesis Testing 200
9.4.1 Calibration Method 200
xiv Contents
9.4.2 Minimum Volatility Method 201
9.5 Two Simulation Studies 202
9.5.1 Univariate Mean 203
9.5.2 Linear Regression 204
9.6 Conclusions 206
9.7 Tables 208
10 Extrapolation, Interpolation, and Higher Order Accuracy 213
10.1 Introduction 213
10.2 Background 216
10.3 I.I.D. Data: The Sample Mean 218
10.3.1 Finite Population Correction 218
10.3.2 The Studentized Sample Mean 219
10.3.3 Estimation of a Two Sided Distribution 220
10.3.4 Extrapolation 221
10.3.5 Robust Interpolation 224
10.4 I.I.D. Data: General Statistics 225
10.4.1 Extrapolation 225
10.4.2 Case of Unknown Convergence Rate to the
Asymptotic Approximation 226
10.5 Strong Mixing Data 228
10.5.1 The Studentized Sample Mean 228
10.5.2 Estimation of a Two Sided Distribution 231
10.5.3 The Unstudentized Sample Mean and the General
Extrapolation Result 232
10.5.4 Finite Population Correction in the Mixing Case . 235
10.5.5 Bias Corrected Variance Estimation for Strong
Mixing Data 236
10.6 Moderate Deviations in Subsampling Distribution
Estimation 244
10.7 Conclusions 251
11 Subsampling the Mean with Heavy Tails 253
11.1 Introduction 253
11.2 Stable Distributions 254
11.3 Extension of Previous Theory 257
11.4 Subsampling Inference for the Mean with Heavy Tails . . 260
11.4.1 Appealing to a Limiting Stable Law 260
11.4.2 Using Self Normalizing Sums 263
11.5 Choice of the Block Size 265
11.6 Simulation Study 266
11.7 Conclusions 267
11.8 Tables 269
Contents xv
12 Subsampling the Autoregressive Parameter 270
12.1 Introduction 270
12.2 Extension of Previous Theory 272
12.2.1 The Basic Method 272
12.2.2 Subsampling Studentized Statistics 274
12.3 Subsampling Inference for the Autoregressive Root . 278
12.4 Choice of the Block Size 284
12.5 Simulation Study 286
12.6 Conclusions 287
12.7 Tables 289
13 Subsampling Stock Returns 291
13.1 Introduction 291
13.2 Background and Definitions 292
13.2.1 The GMM Approach 293
13.2.2 The VAR Approach 294
13.2.3 A Bootstrap Approach 296
13.3 The Subsampling Approach 297
13.4 Two Simulation Studies 298
13.4.1 Simulating VAR Data 299
13.4.2 Simulating Bootstrap Data 301
13.5 A New Look at Return Regressions 302
13.6 Additional Looks at Return Regressions 303
13.6.1 A Reorganization of Long Horizon Regressions . . 303
13.6.2 A Joint Test for Multiple Return Horizons 305
13.7 Conclusions 307
13.8 Tables 308
Appendices 315
A Some Results on Mixing 315
B A General Central Limit Theorem 321
References 327
Bibliography 327
Index of Names 341
Index of Subjects 345 |
| any_adam_object | 1 |
| author | Politēs, Kōnstantinos D. 1958- Romano, Joseph P. 1960- Wolf, Michael |
| author_GND | (DE-588)1229009663 (DE-588)12146878X |
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| ctrlnum | (OCoLC)41070657 (DE-599)BVBBV012684791 |
| dewey-full | 519.5/44 519.5/4421 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/44 519.5/44 21 |
| dewey-search | 519.5/44 519.5/44 21 |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| format | Book |
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| indexdate | 2025-03-20T15:01:05Z |
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| language | English |
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| spelling | Politēs, Kōnstantinos D. 1958- Verfasser (DE-588)1229009663 aut Subsampling Dimitris N. Politis ; Joseph P. Romano ; Michael Wolf New York, N.Y. [u.a.] Springer 1999 XV, 347 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Springer series in statistics Hier auch später erschienene, unveränderte Nachdrucke Boostrap jacknife re-amostragem larpcal Bootstrap (Statistique) Bootstrap (Statistique) ram Bootstrap (statistiek) gtt Steekproeven gtt Bootstrap (Statistics) Bootstrap-Statistik (DE-588)4139168-8 gnd rswk-swf Teilstichprobenverfahren (DE-588)4563957-7 gnd rswk-swf Teilstichprobenverfahren (DE-588)4563957-7 s DE-604 Bootstrap-Statistik (DE-588)4139168-8 s Romano, Joseph P. 1960- Verfasser (DE-588)12146878X aut Wolf, Michael Verfasser aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008621707&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Politēs, Kōnstantinos D. 1958- Romano, Joseph P. 1960- Wolf, Michael Subsampling Boostrap jacknife re-amostragem larpcal Bootstrap (Statistique) Bootstrap (Statistique) ram Bootstrap (statistiek) gtt Steekproeven gtt Bootstrap (Statistics) Bootstrap-Statistik (DE-588)4139168-8 gnd Teilstichprobenverfahren (DE-588)4563957-7 gnd |
| subject_GND | (DE-588)4139168-8 (DE-588)4563957-7 |
| title | Subsampling |
| title_auth | Subsampling |
| title_exact_search | Subsampling |
| title_full | Subsampling Dimitris N. Politis ; Joseph P. Romano ; Michael Wolf |
| title_fullStr | Subsampling Dimitris N. Politis ; Joseph P. Romano ; Michael Wolf |
| title_full_unstemmed | Subsampling Dimitris N. Politis ; Joseph P. Romano ; Michael Wolf |
| title_short | Subsampling |
| title_sort | subsampling |
| topic | Boostrap jacknife re-amostragem larpcal Bootstrap (Statistique) Bootstrap (Statistique) ram Bootstrap (statistiek) gtt Steekproeven gtt Bootstrap (Statistics) Bootstrap-Statistik (DE-588)4139168-8 gnd Teilstichprobenverfahren (DE-588)4563957-7 gnd |
| topic_facet | Boostrap jacknife re-amostragem Bootstrap (Statistique) Bootstrap (statistiek) Steekproeven Bootstrap (Statistics) Bootstrap-Statistik Teilstichprobenverfahren |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008621707&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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