Limit theorems for stochastic processes:
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
[2003]
|
| Edition: | Second edition |
| Series: | Die Grundlehren der mathematischen Wissenschaften
288 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XX, 660 Seiten Illustrationen |
| ISBN: | 3540439323 9783540439325 9783662052655 |
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| 245 | 1 | 0 | |a Limit theorems for stochastic processes |c Jean Jacod ; Albert N. Shiryaev |
| 250 | |a Second edition | ||
| 264 | 1 | |a Berlin [u.a.] |b Springer |c [2003] | |
| 264 | 4 | |c © 2003 | |
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| 650 | 4 | |a Semimartingales (Mathématiques) | |
| 650 | 7 | |a Stochastische processen |2 gtt | |
| 650 | 4 | |a Théorèmes limites (Théorie des probabilités) | |
| 650 | 4 | |a Semimartingales (Mathematics) | |
| 650 | 4 | |a Limit theorems (Probability theory) | |
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Record in the Search Index
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JEAN JACOD ALBERT N. SHIRYAEV LIMIT THEOREMS FOR STOCHASTIC PROCESSES
SECOND EDITION SPRINGER TABLE OF CONTENTS CHAPTER I. THE GENERAL THEORY
OF STOCHASTIC PROCESSES, SEMIMARTINGALES AND STOCHASTIC INTEGRALS 1 1.
STOCHASTIC BASIS, STOPPING TIMES, OPTIONAL A-FIELD, MARTINGALES 1 §LA.
STOCHASTIC BASIS 2 §LB. STOPPING TIMES 4 §LC. THE OPTIONAL A-FIELD 5
§LD. THELOCALIZATION PROCEDURE 8 §LE. MARTINGALES 10 §LF. THE DISCRETE
CASE . 13 2. PREDICTABLE A-FIELD, PREDICTABLE TIMES 16 §2A. THE
PREDICTABLE A-FIELD 16 §2B. PREDICTABLE TIMES 17 §2C. TOTALLY
INACCESSIBLE STOPPING TIMES 20 §2D. PREDICTABLE PROJECTION 22 §2E. THE
DISCRETE CASE 25 3. INCREASING PROCESSES 27 §3A. BASIC PROPERTIES 27
§3B. DOOB-MEYER DECOMPOSITION AND COMPENSATORS OF INCREASING PROCESSES
32 §3C. LENGLART DOMINATION PROPERTY 35 §3D. THE DISCRETE CASE 36 4.
SEMIMARTINGALES AND STOCHASTIC INTEGRALS 38 §4A. LOCALLY
SQUARE-INTEGRABLE MARTINGALES 38 §4B. DECOMPOSITIONS OF A LOCAL
MARTINGALE 40 §4C. SEMIMARTINGALES 43 §4D. CONSTRUCTION OF THE
STOCHASTIC INTEGRAL 46 §4E. QUADRATIC VARIATION OF A SEMIMARTINGALE AND
ITO'S FORMULA . 51 §4F. DOLEANS-DADE EXPONENTIAL FORMULA 58 §4G. THE
DISCRETE CASE 62 XIV TABLE OF CONTENTS CHAPTER IL CHARACTERISTICS OF
SEMIMARTINGALES AND PROCESSES WITH INDEPENDENT INCREMENTS 64 1. RANDOM
MEASURES 64 §LA. GENERAL RANDOM MEASURES 65 §LB. INTEGER-VALUED RANDOM
MEASURES 68 §LC. A FUNDAMENTAL EXAMPLE: POISSON MEASURES 70 §LD.
STOCHASTIC INTEGRAL WITH RESPECT TO A RANDOM MEASURE 71 2.
CHARACTERISTICS OF SEMIMARTINGALES 75 §2A. DEFINITION OF THE
CHARACTERISTICS 75 §2B. INTEGRABILITY AND CHARACTERISTICS 81 §2C. A
CANONICAL REPRESENTATION FOR SEMIMARTINGALES 84 §2D. CHARACTERISTICS AND
EXPONENTIAL FORMULA 85 3. SOME EXAMPLES 91 §3A. THE DISCRETE CASE 91
§3B. MORE ON THE DISCRETE CASE 93 §3C. THE "ONE-POINT" POINT PROCESS AND
EMPIRICAL PROCESSES 97 4. SEMIMARTINGALES WITH INDEPENDENT INCREMENTS
101 §4A. WIENER PROCESSES 102 §4B. POISSON PROCESSES AND POISSON RANDOM
MEASURES 103 §4C. PROCESSES WITH INDEPENDENT INCREMENTS AND
SEMIMARTINGALES . 106 §4D. GAUSSIAN MARTINGALES 111 5. PROCESSES WITH
INDEPENDENT INCREMENTS WHICH ARE NOT SEMIMARTINGALES 114 §5A. THE
RESULTS 114 §5B. THEPROOFS 116 6. PROCESSES WITH CONDITIONALLY
INDEPENDENT INCREMENTS 124 7. PROGRESSIVE CONDITIONAL CONTINUOUS PILS
128 8. SEMIMARTINGALES, STOCHASTIC EXPONENTIAL AND STOCHASTIC LOGARITHM
. 134 §8A. MORE ABOUT STOCHASTIC EXPONENTIAL AND STOCHASTIC LOGARITHM.
134 §8B. MULTIPLICATIVE DECOMPOSITIONS AND EXPONENTIALLY SPECIAL
SEMIMARTINGALES 138 CHAPTER III. MARTINGALE PROBLEMS AND CHANGES OF
MEASURES 142 1. MARTINGALE PROBLEMS AND POINT PROCESSES 143 §LA. GENERAL
MARTINGALE PROBLEMS 143 §LB. MARTINGALE PROBLEMS AND RANDOM MEASURES 144
§LC. POINT PROCESSES AND MULTIVARIATE POINT PROCESSES 146 TABLE OF
CONTENTS XV 2. MARTINGALE PROBLEMS AND SEMIMARTINGALES 151 §2A.
FORMULATION OF THE PROBLEM 152 §2B. EXAMPLE: PROCESSES WITH INDEPENDENT
INCREMENTS 154 §2C. DIFFUSION PROCESSES AND DIFFUSION PROCESSES WITH
JUMPS 155 §2D. LOCAL UNIQUENESS 159 3. ABSOLUTELY CONTINUOUS CHANGES OF
MEASURES 165 §3A. THE DENSITY PROCESS 165 §3B. GIRSANOV'S THEOREM FOR
LOCAL MARTINGALES 168 §3C. GIRSANOY'S THEOREM FOR RANDOM MEASURES 170
§3D. GIRSANOV'S THEOREM FOR SEMIMARTINGALES 172 §3E. THE DISCRETE CASE
177 4. REPRESENTATION THEOREM FOR MARTINGALES 179 §4A. STOCHASTIC
INTEGRALS WITH RESPECT TO A MULTI-DIMENSIONAL CONTINUOUS LOCAL
MARTINGALE 179 §4B. PROJECTION OF A LOCAL MARTINGALE ON A RANDOM MEASURE
182 §4C. THE REPRESENTATION PROPERTY 185 §4D. THE FUNDAMENTAL
REPRESENTATION THEOREM 187 5. ABSOLUTELY CONTINUOUS CHANGE OF MEASURES:
EXPLICIT COMPUTATION OF THE DENSITY PROCESS 191 §5A. ALL P-MARTINGALES
HAVE THE REPRESENTATION PROPERTY RELATIVE TO X 192 §5B. P' HA S THE
LOCAL UNIQUENESS PROPERTY 196 §5C. EXAMPLES 200 6. INTEGRALS OF
VECTOR-VALUED PROCESSES AND §6A. STOCHASTIC INTEGRALS WITH RESPECT TO A
MULTI-DIMENSIONAL LOCALLY SQUARE-INTEGRABLE MARTINGALE 204 §6B.
INTEGRALS WITH RESPECT TO A MULTI-DIMENSIONAL PROCESS OF LOCALLY FINITE
VARIATION 206 §6C. STOCHASTIC INTEGRALS WITH RESPECT TO A
MULTI-DIMENSIONAL SEMIMARTINGALE 207 §6D. STOCHASTIC INTEGRALS: A
PREDICTABLE CRITERION 212 §6E. IMOCALIZATION AND CT-MARTINGALES 214 7.
LAPLACE CUMULANT PROCESSES AND ESSCHER'S CHANGE OF MEASURES . 219
§7A. LAPLACE CUMULANT PROCESSES OF EXPONENTIALLY SPECIAL SEMIMARTINGALES
219 §7B. ESSCHER CHANGE OF MEASURE 222 XVI TABLE OF CONTENTS CHAPTER IV.
HELLINGER PROCESSES, ABSOLUTE CONTINUITY AND SINGULARITY OF MEASURES 227
1. HELLINGER INTEGRALS AND HELLINGER PROCESSES 228 §LA.
KAKUTANI-HELLINGER DISTANCE AND HELLINGER INTEGRALS 228 §LB. HELLINGER
PROCESSES 230 §LC. COMPUTATION OF HELLINGER PROCESSES IN TERMS OF THE
DENSITY PROCESSES 234 §LD. SOME OTHER PROCESSES OF INTEREST 237 §LE. THE
DISCRETE CASE 242 2. PREDICTABLE CRITERIA FOR ABSOLUTE CONTINUITY AND
SINGULARITY 245 §2A. STATEMENT OF THE RESULTS 245 §2B. THE PROOFS 248
§2C. THE DISCRETE CASE 252 3. HELLINGER PROCESSES FOR SOLUTIONS OF
MARTINGALE PROBLEMS 254 §3A. THE GENERAL SETTING 255 §3B. THE CASE WHERE
P AND P' ARE DOMINATED BY A MEASURE HAVING THE MARTINGALE REPRESENTATION
PROPERTY 257 §3C. THE CASE WHERE LOCAL UNIQUENESS HOLDS 266 4. EXAMPLES
272 §4A. POINT PROCESSES AND MULTIVARIATE POINT PROCESSES 272 §4B.
GENERALIZED DIFFUSION PROCESSES 275 §4C. PROCESSES WITH INDEPENDENT
INCREMENTS 277 CHAPTER V. CONTIGUITY, ENTIRE SEPARATION, CONVERGENCE IN
VARIATION . . 284 1. CONTIGUITY AND ENTIRE SEPARATION 284 §LA. GENERAL
FACTS 284 §LB. CONTIGUITY AND FILTRATIONS 290 2. PREDICTABLE CRITERIA
FOR CONTIGUITY AND ENTIRE SEPARATION 291 §2A. STATEMENTS OF THE RESULTS
291 §2B. THE PROOFS 294 §2C. THE DISCRETE CASE 301 3. EXAMPLES 304 §3A.
POINT PROCESSES 304 §3B. GENERALIZED DIFFUSION PROCESSES 305 §3C.
PROCESSES WITH INDEPENDENT INCREMENTS 306 4. VARIATION METRIE 309 §4A.
VARIATION METRIE AND HELLINGER INTEGRALS 310 §4B. VARIATION METRIE AND
HELLINGER PROCESSES 312 TABLE OF CONTENTS XVII §4C. EXAMPLES: POINT
PROCESSES AND MULTIVARIATE POINT PROCESSES . 318 §4D. EXAMPLE:
GENERALIZED DIFFUSION PROCESSES 322 CHAPTER VI. SKOROKHOD TOPOLOGY AND
CONVERGENCE OF PROCESSES 324 1. THE SKOROKHOD TOPOLOGY 325 §LA.
INTRODUCTION AND NOTATION 325 §LB. THE SKOROKHOD TOPOLOGY: DEFINITION
AND MAIN RESULTS 327 §LC. PROOF OF THEOREM 1.14 329 2. CONTINUITY FOR
THE SKOROKHOD TOPOLOGY 337 §2A. CONTINUITY PROPERTIES OF SOME FUNCTIONS
337 §2B. INCREASING FUNCTIONS AND THE SKOROKHOD TOPOLOGY 342 3. WEAK
CONVERGENCE 347 §3A. WEAK CONVERGENCE OF PROBABILITY MEASURES 347 §3B.
APPLICATION TO CAEDLAEG PROCESSES 348 4. CRITERIA FOR TIGHTNESS: THE
QUASI-LEFT CONTINUOUS CASE 355 §4A. ALDOUS' CRITERION FOR TIGHTNESS 356
§4B. APPLICATION TO MARTINGALES AND SEMIMARTINGALES 358 5. CRITERIA FOR
TIGHTNESS: THE GENERAL CASE 362 §5A. CRITERIA FOR SEMIMARTINGALES 362
§5B. AN AUXILIARY RESULT 365 §5C. PROOF OF THEOREM 5.17 367 6.
CONVERGENCE, QUADRATIC VARIATION, STOCHASTIC INTEGRALS 376 §6A. THE P-UT
CONDITION 377 §6B. TIGHTNESS AND THE P-UT PROPERTY 382 §6C. CONVERGENCE
OF STOCHASTIC INTEGRALS AND QUADRATIC VARIATION . 382 §6D. SOME
ADDITIONAL RESULTS 386 CHAPTER VII. CONVERGENCE OF PROCESSES WITH
INDEPENDENT INCREMENTS . 389 1. INTRODUCTION TO FUNCTIONAL LIMIT
THEOREMS 390 2. FINITE-DIMENSIONAL CONVERGENCE 394 §2A. CONVERGENCE OF
INFINITELY DIVISIBLE DISTRIBUTIONS 394 §2B. SOME LEMMAS ON
CHARACTERISTIC FUNCTIONS 398 §2C. CONVERGENCE OFROWWISE INDEPENDENT
TRIANGULAER ARRAYS 402 §2D. FINITE-DIMENSIONAL CONVERGENCE OF
PH-SEMIMARTINGALES TO A PII WITHOUT FIXED TIME OF DISCONTINUITY 408 3.
FUNCTIONAL CONVERGENCE AND CHARACTERISTICS 413 §3A. THE RESULTS 414 §3B.
SUFFICIENT CONDITION FOR CONVERGENCE UNDER 2.48 418 XVIII TABLE OF
CONTENTS §3C. NECESSARY CONDITION FOR CONVERGENCE 418 §3D. SUFFICIENT
CONDITION FOR CONVERGENCE 424 4. MORE ON THE GENERAL CASE 428 §4A.
CONVERGENCE OF NON-INFINITESIMAL ROWWISE INDEPENDENT ARRAYS . 428 §4B.
FINITE-DIMENSIONAL CONVERGENCE FOR GENERAL PII 436 §4C. ANOTHER
NECESSARY AND SUFFICIENT CONDITION FOR FUNCTIONAL CONVERGENCE 439 5. THE
CENTRAL LIMIT THEOREM 444 §5A. THE LINDEBERG-FELLER THEOREM 445 §5B.
ZOLOTAREV'S TYPE THEOREMS 446 §5C. FINITE-DIMENSIONAL CONVERGENCE OF
PII'S TO A GAUSSIAN MARTINGALE 450 §5D. FUNCTIONAL CONVERGENCE OF PII'S
TO A GAUSSIAN MARTINGALE 452 CHAPTER VIII. CONVERGENCE TO A PROCESS WITH
INDEPENDENT INCREMENTS . 456 1. FINITE-DIMENSIONAL CONVERGENCE, A
GENERAL THEOREM 456 §LA. DESCRIPTION OF THE SETTING FOR THIS CHAPTER 456
§LB. THE BASIC THEOREM 457 §LC. REMARKS AND COMMENTS 459 2. CONVERGENCE
TO A PII WITHOUT FIXED TIME OF DISCONTINUITY 460 §2A. FINITE-DIMENSIONAL
CONVERGENCE 461 §2B. FUNCTIONAL CONVERGENCE 464 §2C. APPLICATION TO
TRIANGULAER ARRAYS 465 §2D. OTHER CONDITIONS FOR CONVERGENCE 467 3.
APPLICATIONS 469 §3A. CENTRAL LIMIT THEOREM: NECESSARY AND SUFFICIENT
CONDITIONS . . 470 §3B. CENTRAL LIMIT THEOREM: THE MARTINGALE CASE 473
§3C. CENTRAL LIMIT THEOREM FOR TRIANGULAER ARRAYS 477 §3D. CONVERGENCE OF
POINT PROCESSES 478 §3E. NORMED SUMS OF I.I.D. SEMIMARTINGALES 481 §3F.
LIMIT THEOREMS FOR FUNCTIONALS OF MARKOV PROCESSES 486 §3G. LIMIT
THEOREMS FOR STATIONARY PROCESSES 489 4. CONVERGENCE TO A GENERAL
PROCESS WITH INDEPENDENT INCREMENTS . 499 §4A. PROOF OFTHEOREM 4.1
WHEN THE CHARACTERISTIC FUNCTION OF X, VANISHES ALMOST NOWHERE 501 §4B.
CONVERGENCE OF POINT PROCESSES 503 §4C. CONVERGENCE TO A GAUSSIAN
MARTINGALE 504 TABLE OF CONTENTS XIX 5. CONVERGENCE TO A MIXTURE OF
PII'S, STAHLE CONVERGENCE AND MIXING CONVERGENCE 506 §5A. CONVERGENCE TO
A MIXTURE OF PII'S 506 §5B. MORE ON THE CONVERGENCE TO A MIXTURE OF
PII'S 510 §5C. STAHLE CONVERGENCE 512 §5D. MIXING CONVERGENCE 518 §5E.
APPLICATION TO STATIONARY PROCESSES 519 CHAPTER IX. CONVERGENCE TO A
SEMIMARTINGALE 521 1. LIMITS OF MARTINGALES 521 §LA. THE BOUNDED CASE
522 §LB. THEUNBOUNDED CASE 524 2. IDENTIFICATION OF THE LIMIT 527 §2A.
INTRODUCTORY REMARKS 527 §2B. IDENTIFICATION OF THE LIMIT: THE MAIN
RESULT 530 §2C. IDENTIFICATION OF THE LIMIT VIA CONVERGENCE OF THE
CHARACTERISTICS 533 §2D. APPLICATION: EXISTENCE OF SOLUTIONS TO SOME
MARTINGALE PROBLEMS 535 3. LIMIT THEOREMS FOR SEMIMARTINGALES 540 §3A.
TIGHTNESS OF THE SEQUENCE (X") 541 §3B. LIMIT THEOREMS: THE BOUNDED CASE
546 §3C. LIMIT THEOREMS: THE LOCALLY BOUNDED CASE 550 4. APPLICATIONS
554 §4A. CONVERGENCE OF DIFFUSION PROCESSES WITH JUMPS 554 §4B.
CONVERGENCE OF STEP MARKOV PROCESSES TO DIFFUSIONS 557 §4C. EMPIRICAL
DISTRIBUTIONS AND BROWNIAN BRIDGE 560 §4D. CONVERGENCE TO A CONTINUOUS
SEMIMARTINGALE: NECESSARY AND SUFFICIENT CONDITIONS 561 5. CONVERGENCE
OF STOCHASTIC INTEGRALS 564 §5A. CHARACTERISTICS OF STOCHASTIC INTEGRALS
564 §5B. STATEMENT OF THE RESULTS 567 §5C. THE PROOFS 570 6. STABILITY
FOR STOCHASTIC DIFFERENTIAL EQUATION 575 §6A. AUXILIARY RESULTS 576 §6B.
STOCHASTIC DIFFERENTIAL EQUATIONS 577 §6C. STABILITY 578 XX TABLE OF
CONTENTS 7. STAHLE CONVERGENCE TO A PROGRESSIVE CONDITIONAL CONTINUOUS
PII. 583 §7A. A GENERAL RESULT 583 §7B. CONVERGENCE OF DISCRETIZED
PROCESSES 589 CHAPTER X. LIMIT THEOREMS, DENSITY PROCESSES AND
CONTIGUITY 592 1. CONVERGENCE OF THE DENSITY PROCESSES TO A CONTINUOUS
PROCESS 593 §LA. INTRODUCTION, STATEMENT OF THE MAIN RESULTS 593 §LB. AN
AUXILIARY COMPUTATION 597 §LC. PROOFS OF THEOREMS 1.12 AND 1.16 603 §LD.
CONVERGENCE TO THE EXPONENTIAL OF A CONTINUOUS MARTINGALE . 606 §LE.
CONVERGENCE IN TERMS OF HELLINGER PROCESSES 609 2. CONVERGENCE OF THE
LOG-LIKELIHOOD TO A PROCESS WITH INDEPENDENT INCREMENTS 612 §2A.
INTRODUCTION, STATEMENT OF THE RESULTS 612 §2B. THE PROOF OF THEOREM
2.12 615 §2C. EXAMPLE: POINT PROCESSES 619 3. THE STATISTICAL INVARIANCE
PRINCIPLE 620 §3A. GENERAL RESULTS 621 §3B. CONVERGENCE TO A GAUSSIAN
MARTINGALE 623 BIBLIOGRAPHICAL COMMENTS 629 REFERENCES 641 INDEX OF
SYMBOLS 653 INDEX OF TERMINOLOGY 655 INDEX OF TOPICS 659 INDEX OF
CONDITIONS FOR LIMIT THEOREMS 661 |
| any_adam_object | 1 |
| author | Jacod, Jean 1944- Širjaev, Alʹbert N. 1934- |
| author_GND | (DE-588)140772421 (DE-588)12203502X |
| author_facet | Jacod, Jean 1944- Širjaev, Alʹbert N. 1934- |
| author_role | aut aut |
| author_sort | Jacod, Jean 1944- |
| author_variant | j j jj a n š an anš |
| building | Verbundindex |
| bvnumber | BV017759180 |
| callnumber-first | Q - Science |
| callnumber-label | QA274 |
| callnumber-raw | QA274.5.J33 2003 |
| callnumber-search | QA274.5.J33 2003 |
| callnumber-sort | QA 3274.5 J33 42003 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | SK 820 QH 237 SK 800 |
| classification_tum | MAT 604f MAT 605f |
| ctrlnum | (OCoLC)50554399 (DE-599)BVBBV017759180 |
| dewey-full | 519.2/87 519.2/8721 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.2/87 519.2/87 21 |
| dewey-search | 519.2/87 519.2/87 21 |
| dewey-sort | 3519.2 287 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | Second edition |
| format | Book |
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| id | DE-604.BV017759180 |
| illustrated | Illustrated |
| indexdate | 2024-08-30T00:13:13Z |
| institution | BVB |
| isbn | 3540439323 9783540439325 9783662052655 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-010667700 |
| oclc_num | 50554399 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM DE-19 DE-BY-UBM DE-521 DE-384 DE-83 DE-11 DE-29T DE-188 DE-20 |
| owner_facet | DE-91G DE-BY-TUM DE-19 DE-BY-UBM DE-521 DE-384 DE-83 DE-11 DE-29T DE-188 DE-20 |
| physical | XX, 660 Seiten Illustrationen |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Springer |
| record_format | marc |
| series | Die Grundlehren der mathematischen Wissenschaften |
| series2 | Die Grundlehren der mathematischen Wissenschaften |
| spelling | Jacod, Jean 1944- (DE-588)140772421 aut Limit theorems for stochastic processes Jean Jacod ; Albert N. Shiryaev Second edition Berlin [u.a.] Springer [2003] © 2003 XX, 660 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Die Grundlehren der mathematischen Wissenschaften 288 Limiettheorema's gtt Semimartingales (Mathématiques) Stochastische processen gtt Théorèmes limites (Théorie des probabilités) Semimartingales (Mathematics) Limit theorems (Probability theory) Semimartingal (DE-588)4180967-1 gnd rswk-swf Stochastischer Prozess (DE-588)4057630-9 gnd rswk-swf Grenzwertsatz (DE-588)4158163-5 gnd rswk-swf Semimartingal (DE-588)4180967-1 s Grenzwertsatz (DE-588)4158163-5 s DE-604 Stochastischer Prozess (DE-588)4057630-9 s 1\p DE-604 Širjaev, Alʹbert N. 1934- (DE-588)12203502X aut Erscheint auch als Online-Ausgabe 978-3-662-05265-5 Die Grundlehren der mathematischen Wissenschaften 288 (DE-604)BV000000395 288 GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010667700&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Jacod, Jean 1944- Širjaev, Alʹbert N. 1934- Limit theorems for stochastic processes Die Grundlehren der mathematischen Wissenschaften Limiettheorema's gtt Semimartingales (Mathématiques) Stochastische processen gtt Théorèmes limites (Théorie des probabilités) Semimartingales (Mathematics) Limit theorems (Probability theory) Semimartingal (DE-588)4180967-1 gnd Stochastischer Prozess (DE-588)4057630-9 gnd Grenzwertsatz (DE-588)4158163-5 gnd |
| subject_GND | (DE-588)4180967-1 (DE-588)4057630-9 (DE-588)4158163-5 |
| title | Limit theorems for stochastic processes |
| title_auth | Limit theorems for stochastic processes |
| title_exact_search | Limit theorems for stochastic processes |
| title_full | Limit theorems for stochastic processes Jean Jacod ; Albert N. Shiryaev |
| title_fullStr | Limit theorems for stochastic processes Jean Jacod ; Albert N. Shiryaev |
| title_full_unstemmed | Limit theorems for stochastic processes Jean Jacod ; Albert N. Shiryaev |
| title_short | Limit theorems for stochastic processes |
| title_sort | limit theorems for stochastic processes |
| topic | Limiettheorema's gtt Semimartingales (Mathématiques) Stochastische processen gtt Théorèmes limites (Théorie des probabilités) Semimartingales (Mathematics) Limit theorems (Probability theory) Semimartingal (DE-588)4180967-1 gnd Stochastischer Prozess (DE-588)4057630-9 gnd Grenzwertsatz (DE-588)4158163-5 gnd |
| topic_facet | Limiettheorema's Semimartingales (Mathématiques) Stochastische processen Théorèmes limites (Théorie des probabilités) Semimartingales (Mathematics) Limit theorems (Probability theory) Semimartingal Stochastischer Prozess Grenzwertsatz |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010667700&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000000395 |
| work_keys_str_mv | AT jacodjean limittheoremsforstochasticprocesses AT sirjaevalʹbertn limittheoremsforstochasticprocesses |