Maximum penalized likelihood estimation: 1 Density estimation
Gespeichert in:
Hauptverfasser: | , |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
New York [u.a.]
Springer
2001
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Schriftenreihe: | Springer series in statistics
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Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | XVII, 510 S. graph. Darst. |
ISBN: | 0387952683 |
Internformat
MARC
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Datensatz im Suchindex
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adam_text | P.P.B. EGGERMONT V.N. LARICCIA MAXIMUM PENALIZED LIKELIHOOD ESTIMATION
VOLUME I: DENSITY ESTIMATION WITH 30 FIGURES SPRINGER CONTENTS PREFACE
VII NOTATIONS, ACRONYMS, AND CONVENTIONS XV 1. PARAMETRIC AND
NONPARAMETRIC ESTIMATION 1 1. INTRODUCTION 1 2. INDIRECT PROBLEMS, EM
ALGORITHMS, KERNEL DENSITY ESTIMATION, AND ROUGHNESS PENALIZATION 8 3.
CONSISTENCY OF NONPARAMETRIC ESTIMATORS 13 4. THE USUAL NONPARAMETRIC
ASSUMPTIONS 18 5. PARAMETRIC VS NONPARAMETRIC RATES 20 6. SIEVES AND
CONVEXITY 22 7. ADDITIONAL NOTES AND COMMENTS 26 PART I: PARAMETRIC
ESTIMATION 2. PARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION 29 1.
INTRODUCTION 29 2. OPTIMALITY OF MAXIMUM LIKELIHOOD ESTIMATORS 37 3.
COMPUTING MAXIMUM LIKELIHOOD ESTIMATORS 49 4. THE EM ALGORITHM 53 5.
SENSITIVITY TO ERRORS: M-ESTIMATORS 63 6. RIDGE REGRESSION 75 7.
RIGHT-SKEWED DISTRIBUTIONS WITH HEAVY TAILS 80 8. ADDITIONAL COMMENTS 88
3. PARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION IN ACTION 91 1. INTRODUCTION
91 2. BEST ASYMPTOTICALLY NORMAL ESTIMATORS 92 AND SMALL SAMPLE BEHAVIOR
3. MIXTURES OF NORMALS 96 4. COMPUTING WITH THE LOG-NORMAL DISTRIBUTION
101 5. ON CHOOSING PARAMETRIC FAMILIES OF DISTRIBUTIONS 104 6. TOWARD
NONPARAMETRICS: MIXTURES REVISITED 113 CONTENTS PART II: NONPARAMETRIC
ESTIMATION 4. KERNEL DENSITY ESTIMATION 119 1. INTRODUCTION 119 2. THE
EXPECTED L 1 ERROR IN KERNEL DENSITY ESTIMATION 130 3. INTEGRATION BY
PARTS TRICKS 136 4. SUBMARTINGALES, EXPONENTIAL INEQUALITIES, 139 AND
ALMOST SURE BOUNDS FOR THE L 1 ERROR 5. ALMOST SURE BOUNDS FOR
EVERYTHING ELSE 151 6. NONPARAMETRIC ESTIMATION OF ENTROPY 159 7.
OPTIMAL KERNELS 167 8. ASYMPTOTIC NORMALITY OF THE L 1 ERROR 173 9.
ADDITIONAL COMMENTS 186 5. NONPARAMETRIC MAXIMUM PENALIZED LIKELIHOOD
ESTIMATION 187 1. INTRODUCTION 187 2. GOOD S ROUGHNESS PENALIZATION OF
ROOT-DENSITIES 189 3. ROUGHNESS PENALIZATION OF LOG-DENSITIES 202 4.
ROUGHNESS PENALIZATION OF BOUNDED LOG-DENSITIES 207 5. ESTIMATION UNDER
CONSTRAINTS 213 6. ADDITIONAL NOTES AND COMMENTS 218 6. MONOTONE AND
UNIMODAL DENSITIES 221 1. INTRODUCTION 221 2. MONOTONE DENSITY
ESTIMATION 225 3. ESTIMATING SMOOTH MONOTONE DENSITIES 232 4. ALGORITHMS
AND CONTRACTIVITY 234 5. CONTRACTIVITY: THE GENERAL CASE 244 6.
ESTIMATING SMOOTH UNIMODAL DENSITIES 250 7. OTHER UNIMODAL DENSITY
ESTIMATORS 262 8. AFTERTHOUGHTS: CONVEX DENSITIES 265 9. ADDITIONAL
NOTES AND COMMENTS 267 7. CHOOSING THE SMOOTHING PARAMETER 271 1.
INTRODUCTION 271 2. LEAST-SQUARES CROSS-VALIDATION AND PLUG-IN METHODS
276 3. THE DOUBLE KERNEL METHOD 283 4. ASYMPTOTIC PLUG-IN METHODS 295 5.
AWAY WITH PILOT ESTIMATORS!? 299 6. A DISCREPANCY PRINCIPLE 306 7. THE
GOOD ESTIMATOR 309 8. ADDITIONAL NOTES AND COMMENTS 316 8. NONPARAMETRIC
DENSITY ESTIMATION IN ACTION 319 1. INTRODUCTION 319 2.
FINITE-DIMENSIONAL APPROXIMATIONS 320 3. SMOOTHING PARAMETER SELECTION
323 4. TWO DATA SETS 329 CONTENTS XIII 5. KERNEL SELECTION 333 6.
UNIMODAL DENSITY ESTIMATION 338 PART III: CONVEXITY 9. CONVEX
OPTIMIZATION IN FINITE- 347 DIMENSIONAL SPACES 1. CONVEX SETS AND CONVEX
FUNCTIONS 347 2. CONVEX MINIMIZATION PROBLEMS 357 3. LAGRANGE
MULTIPLIERS 361 4. STRICT AND STRONG CONVEXITY 370 5. COMPACTNESS
ARGUMENTS 373 6. ADDITIONAL NOTES AND COMMENTS 375 10. CONVEX
OPTIMIZATION IN INFINITE- 377 DIMENSIONAL SPACES 1. CONVEX FUNCTIONS 377
2. CONVEX INTEGRALS 383 3. STRONG CONVEXITY 387 4. COMPACTNESS ARGUMENTS
390 5. EULER EQUATIONS 395 6. FINITELY MANY CONSTRAINTS 398 7.
ADDITIONAL NOTES AND COMMENTS 402 11. CONVEXITY IN ACTION 405 1.
INTRODUCTION 405 2. OPTIMAL KERNELS 405 3. DIRECT NONPARAMETRIC MAXIMUM
ROUGHNESS 412 PENALIZED LIKELIHOOD DENSITY ESTIMATION 4. EXISTENCE OF
ROUGHNESS PENALIZED LOG-DENSITIES 417 5. EXISTENCE OF LOG-CONCAVE
ESTIMATORS 423 6. CONSTRAINED MINIMUM DISTANCE ESTIMATION 425 APPENDICES
1. SOME DATA SETS 433 1. INTRODUCTION 433 2. THE OLD FAITHFUL GEYSER
DATA 433 3. THE BUFFALO SNOW FALL DATA 434 4. THE RUBBER ABBRASION DATA
434 5. CLOUD SEEDING DATA 434 6. TEXO OIL FIELD DATA 435 2. THE FOURIER
TRANSFORM 437 1. INTRODUCTION 437 2. SMOOTH FUNCTIONS 437 3. INTEGRABLE
FUNCTIONS 441 4. SQUARE INTEGRABLE FUNCTIONS 443 5. SOME EXAMPLES 446 6.
THE WIENER THEOREM FOR ***.) 456 XIV CONTENTS 3. BANACH SPACES, DUAL
SPACES, AND COMPACTNESS 459 1. BANACH SPACES 459 2. BOUNDED LINEAR
OPERATORS 462 3. COMPACT OPERATORS 463 4. DUAL SPACES 469 5. HILBERT
SPACES 472 6. COMPACT HERMITIAN OPERATORS 478 7. REPRODUCING KERNEL
HILBERT SPACES 484 8. CLOSING COMMENTS 485 REFERENCES 487 AUTHOR INDEX
499 SUBJECT INDEX 505
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any_adam_object | 1 |
author | Eggermont, Paulus P. B. La Riccia, Vincent N. |
author_facet | Eggermont, Paulus P. B. La Riccia, Vincent N. |
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bvnumber | BV013902901 |
classification_rvk | QH 233 SK 835 |
ctrlnum | (OCoLC)174770900 (DE-599)BVBBV013902901 |
discipline | Mathematik Wirtschaftswissenschaften |
format | Book |
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indexdate | 2024-07-09T18:54:10Z |
institution | BVB |
isbn | 0387952683 |
language | English |
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physical | XVII, 510 S. graph. Darst. |
publishDate | 2001 |
publishDateSearch | 2001 |
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publisher | Springer |
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series2 | Springer series in statistics |
spelling | Eggermont, Paulus P. B. Verfasser aut Maximum penalized likelihood estimation 1 Density estimation P. P. B. Eggermont ; V. N. LaRiccia New York [u.a.] Springer 2001 XVII, 510 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Springer series in statistics La Riccia, Vincent N. Verfasser aut (DE-604)BV013902900 1 GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009514386&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Eggermont, Paulus P. B. La Riccia, Vincent N. Maximum penalized likelihood estimation |
title | Maximum penalized likelihood estimation |
title_auth | Maximum penalized likelihood estimation |
title_exact_search | Maximum penalized likelihood estimation |
title_full | Maximum penalized likelihood estimation 1 Density estimation P. P. B. Eggermont ; V. N. LaRiccia |
title_fullStr | Maximum penalized likelihood estimation 1 Density estimation P. P. B. Eggermont ; V. N. LaRiccia |
title_full_unstemmed | Maximum penalized likelihood estimation 1 Density estimation P. P. B. Eggermont ; V. N. LaRiccia |
title_short | Maximum penalized likelihood estimation |
title_sort | maximum penalized likelihood estimation density estimation |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009514386&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
volume_link | (DE-604)BV013902900 |
work_keys_str_mv | AT eggermontpauluspb maximumpenalizedlikelihoodestimation1 AT laricciavincentn maximumpenalizedlikelihoodestimation1 |