Statistical modelling and regression structures: Festschrift in honour of Ludwig Fahrmeir
Gespeichert in:
| Weitere beteiligte Personen: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin [u.a.]
Physica-Verl.
2010
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020195344&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XXIV, 472 S. Ill., graph. Darst. |
| ISBN: | 9783790824124 |
Internformat
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| 245 | 1 | 0 | |a Statistical modelling and regression structures |b Festschrift in honour of Ludwig Fahrmeir |c Thomas Kneib ... ed. |
| 264 | 1 | |a Berlin [u.a.] |b Physica-Verl. |c 2010 | |
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Datensatz im Suchindex
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CONTENTS LIST OF CONTRIBUTORS XIX THE SMOOTH COMPLEX LOGARITHM AND
QUASI-PERIODIC MODELS 1 PAUL H. C. EILERS 1 FOREWORD 1 2 INTRODUCTION 1
3 DATA AND MODELS 2 3.1 THE BASIC MODEL 3 3.2 SPLINES AND PENALTIES 3
3.3 STARTING VALUES 7 3.4 SIMPLE TREND CORRECTION AND PRIOR
TRANSFORMATION 8 3.5 A COMPLEX SIGNAL 8 3.6 NON-NORMAL DATA AND CASCADED
LINKS 10 3.7 ADDING HARMONICS 11 4 MORE TO EXPLORE 12 5 DISCUSSION 15
REFERENCES 17 P-SPLINE VARYING COEFFICIENT MODELS FOR COMPLEX DATA 19
BRIAN D. MARX 1 INTRODUCTION 19 2 "LARGE SCALE" VCM, WITHOUT BACKFITTING
22 3 NOTATION AND SNAPSHOT OF A SMOOTHING TOOL: B-SPLINES 24 3.1 GENERAL
KNOT PLACEMENT 25 3.2 SMOOTHING THE KTB DATA 25 4 USING B-SPLINES FOR
VARYING COEFFICIENT MODELS 26 5 P-SPLINE SNAPSHOT: EQUALLY-SPACED KNOTS
& PENALIZATION 28 5.1 P-SPLINES FOR ADDITIVE VCMS 30 5.2 STANDARD ERROR
BANDS 30 6 OPTIMALLY TUNING P-SPLINES 31 7 MORE KTB RESULTS 33 8
EXTENDING P-VCM INTO THE GENERALIZED LINEAR MODEL 33 9 TWO-DIMENSIONAL
VARYING COEFFICIENT MODELS 36 BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/998416363 DIGITALISIERT DURCH X CONTENTS 9.1 MECHANICS
OF 2D-VCM THROUGH EXAMPLE 37 9.2 VCMS AND PENALTIES AS ARRAYS 39 9.3
EFFICIENT COMPUTATION USING ARRAY REGRESSION 40 10 DISCUSSION TOWARD
MORE COMPLEX VCMS 41 REFERENCES 42 PENALIZED SPLINES, MIXED MODELS AND
BAYESIAN IDEAS 45 GOERAN KAUERMANN 1 INTRODUCTION 45 2 NOTATION AND
PENALIZED SPLINES AS LINEAR MIXED MODELS 46 3 CLASSIFICATION WITH MIXED
MODELS 48 4 VARIABLE SELECTION WITH SIMPLE PRIORS 50 4.1 MARGINAL AKAIKE
INFORMATION CRITERION 50 4.2 COMPARISON IN LINEAR MODELS 53 4.3
SIMULATION 55 5 DISCUSSION AND EXTENSIONS 56 REFERENCES 57 BAYESIAN
LINEAR REGRESSION * DIFFERENT CONJUGATE MODELS AND THEIR (IN)SENSITIVITY
TO PRIOR-DATA CONFLICT 59 GERO WALTER AND THOMAS AUGUSTIN 1 INTRODUCTION
59 2 PRIOR-DATA CONFLICT IN THE I.I.D. CASE 62 3 THE STANDARD APPROACH
FOR BAYESIAN LINEAR REGRESSION (SCP) . 64 3.1 UPDATE OF SS \ A 2 65 3.2
UPDATE OF A 2 66 3.3 UPDATE OF SS 67 4 AN ALTERNATIVE APPROACH FOR
CONJUGATE PRIORS IN BAYESIAN LINEAR REGRESSION (CCCP) 68 4.1 UPDATE OF SS
\ A 2 71 4.2 UPDATEOFFF 2 71 4.3 UPDATE OF SS 7 CONTENTS XI 4 CONCLUSION
AND OUTLOOK 88 REFERENCES 89 POSTERIOR AND CROSS-VALIDATORY PREDICTIVE
CHECKS: A COMPARISON OF MCMCANDLNLA. 91 LEONHARD HELD, BIRGIT SCHROEDLE
AND HAVARD RUE 1 INTRODUCTION 91 2 THE INLA APPROACH 92 2.1 PARAMETER
ESTIMATION WITH INLA 92 2.2 POSTERIOR PREDICTIVE MODEL CHECKS WITH INLA
94 2.3 LEAVE-ONE-OUT CROSS-VALIDATION WITH INLA 95 3 PREDICTIVE MODEL
CHECKS WITH MCMC 96 3.1 POSTERIOR PREDICTIVE MODEL CHECKS WITH MCMC 97
3.2 LEAVE-ONE-OUT CROSS-VALIDATION WITH MCMC 97 3.3 APPROXIMATE
CROSS-VALIDATION WITH MCMC 98 4 APPLICATION 99 4.1 A COMPARISON OF
POSTERIOR PREDICTIVE MODEL CHECKS 101 4.2 A COMPARISON OF LEAVE-ONE-OUT
CROSS-VALIDATED PREDICTIVE CHECKS , 103 4.3 A COMPARISON OF APPROXIMATE
CROSS-VALIDATION WITH POSTERIOR AND LEAVE-ONE-OUT PREDICTIVE CHECKS
USING MCMC 106 5 DISCUSSION 107 REFERENCES 109 DATA AUGMENTATION AND
MCMC FOR BINARY AND MULTINOMIAL LOGIT MODELS ILL SYLVIA
FRIIHWIRTH-SCHNATTER AND RUDOLF FRIIHWIRTH 1 INTRODUCTION ILL 2 MCMC
ESTIMATION BASED ON DATA AUGMENTATION FOR BINARY LOGIT REGRESSION MODELS
.113 2.1 WRITING THE LOGIT MODEL AS A RANDOM UTILITY MODEL 113 2.2 DATA
AUGMENTATION BASED ON THE RANDOM UTILITY MODEL .114 2. XII CONTENTS
GENERALIZED SEMIPARAMETRIC REGRESSION WITH COVARIATES MEASURED WITH
ERROR 133 THOMAS KNEIB, ANDREAS BREZGER AND CIPRIAN M. CRAINICEANU 1
INTRODUCTION 133 2 SEMIPARAMETRIC REGRESSION MODELS WITH MEASUREMENT
ERROR 135 2.1 OBSERVATION MODEL 135 2.2 MEASUREMENT ERROR MODEL 136 2.3
PRIOR DISTRIBUTIONS 136 3 BAYESIAN INFERENCE 139 3.1 POSTERIOR & FULL
CONDITIONALS 139 3.2 IMPLEMENTATIONAL DETAILS & SOFTWARE 141 4
SIMULATIONS 143 4.1 SIMULATION SETUP 143 4.2 SIMULATION RESULTS 144 5
INCIDENT HEART FAILURE IN THE ARIC STUDY 150 6 SUMMARY 153 REFERENCES
153 DETERMINANTS OF THE SOCIOECONOMIC AND SPATIAL PATTERN OF
UNDERNUTRITION BY SEX IN INDIA: A GEOADDITIVE SEMI-PARAMETRIC REGRESSION
APPROACH . 155 CHRISTIANE BELITZ, JUDITH HUEBNER, STEPHAN KLASEN AND
STEFAN LANG 1 INTRODUCTION 155 2 THE DATA 158 3 MEASUREMENT AND
DETERMINANTS OF UNDERNUTRITION 160 3.1 MEASUREMENT 160 3.2 DETERMINANTS
OF UNDERNUTRITION 161 4 VARIABLES INCLUDED IN THE REGRESSION MODEL 162 5
STATISTICAL METHODOLOGY - SEMIPARAMETRIC REGRESSION ANALYSIS . 167 6
RESULTS 170 7 CONCLUSION 177 REFERENCES 178 BOOSTING FOR ESTIMATING
SPATIALLY STRUCTURED ADDITIVE MODELS 181 NIKOLAY ROBINZONOV AND TORSTEN
HOTHORN 1 INTRODUCTION 181 2 METHODS 183 2. CONTENTS XIII GENERALIZED
LINEAR MIXED MODELS BASED ON BOOSTING 197 GERHARD TUTZ AND ANDREAS GROLL
1 INTRODUCTION 197 2 GENERALIZED LINEAR MIXED MODELS - GLMM 198 3
BOOSTED GENERALIZED LINEAR MIXED MODELS - BGLMM 200 3.1 THE BOOSTING
ALGORITHM 200 3.2 COMPUTATIONAL DETAILS OF BGLMM 202 3.3 SIMULATION
STUDY 207 4 APPLICATION TO CD4 DATA 212 5 CONCLUDING REMARKS 214
REFERENCES 214 MEASUREMENT AND PREDICTORS OF A NEGATIVE ATTITUDE TOWARDS
STATISTICS AMONG LMU STUDENTS 217 CAROLIN STROBL, CHRISTIAN DITTRICH,
CHRISTIAN SEILER, SANDRA HACKENSPERGER AND FRIEDRICH LEISCH 1
INTRODUCTION 217 2 METHOD 219 2.1 PARTICIPANTS 219 2.2 PROCEDURE AND
INSTRUMENT 220 2.3 SOFTWARE 221 3 RESULTS 221 3.1 ITEM ANALYSIS FOR SATS
SCALES 221 3.2 NEGATIVE ATTITUDE INDICATOR 223 3.3 PREDICTORS OF A
NEGATIVE ATTITUDE TOWARDS STATISTICS 224 4 DISCUSSION AND CONCLUSION 227
REFERENCES 229 GRAPHICAL CHAIN MODELS AND THEIR APPLICATION 231 IRIS
PIGEOT, STEPHAN KLASEN AND RONJA FORAITA 1 INTRODUCTION 231 2 GRAPHICAL
CHAIN MODELS 233 3 MODEL SELECTION 235 4 DATA SET 236 4.1 SUMMARY
MEASURES 237 4.2 DEPENDENCE CHAIN 239 5 RESULTS 240 6 DISCUSSION 243
REFERENCES 244 INDIRECT COMPARISON OF INTERACTION GRAPHS 24 XIV CONTENTS
2.3 HIERARCHICAL TESTING 253 2.4 COMPUTATIONAL ISSUES 254 3 EXAMPLE 255
4 DISCUSSION 257 REFERENCES 259 MODELLING, ESTIMATION AND VISUALIZATION
OF MULTIVARIATE DEPENDENCE FOR HIGH-FREQUENCY DATA 267 ERIK BRODIN AND
CLAUDIA KLIIPPELBERG 1 MULTIVARIATE RISK ASSESSMENT FOR EXTREME RISK 267
2 MEASURING EXTREME DEPENDENCE 270 3 EXTREME DEPENDENCE ESTIMATION 280 4
HIGH-FREQUENCY FINANCIAL DATA 285 4.1 CLEANING THE DATA 285 4.2
DESEASONALIZING THE DATA 287 4.3 FILTERING THE DATA 289 4.4 ANALYZING
THE EXTREME DEPENDENCE 291 4.5 DIFFERENT TIMESCALES 294 4.6 DEPENDENCE
UNDER FILTERING 296 5 CONCLUSION 298 REFERENCES 299 ORDINAL- AND
CONTINUOUS-RESPONSE STOCHASTIC VOLATILITY MODELS FOR PRICE CHANGES: AN
EMPIRICAL COMPARISON 301 CLAUDIA CZADO, GERNOT MUELLER AND THI-NGOC-GIAU
NGUYEN 1 INTRODUCTION 301 2 ORDINAL- AND CONTINUOUS-RESPONSE STOCHASTIC
VOLATILITY MODELS . 303 2.1 OS V AND S V MODEL SPECIFICATION AND
INTERPRETATION 303 2.2 BAYESIAN INFERENCE FOR OSV AND SV MODELS 305 2.3
MODEL SELECTION 306 3 APPLICATION 308 3.1 DATA 308 3.2 OSV MODELS 310
3.3 SV MODELS 315 3.4 COMPARISON BETWEEN OSV AND SV MODELS 316 4 SUMMARY
AND DISCUSSION 319 REFERENCES 320 COPULA CHOICE WITH FACTOR CREDIT
PORTFOLIO MODELS 32 APPENDIX 372 CONTENTS XV 3.1 THE TEST EXPLAINED 326
3.2 DISCRETE PIT 326 4 SIMULATION STUDY AND ANALYSES 328 4.1 DEFAULT
COUNT DISTRIBUTIONS 328 4.2 POWER TESTS 330 5 CONCLUSION 335 REFERENCES
335 PENALIZED ESTIMATION FOR INTEGER AUTOREGRESSIVE MODELS 337
KONSTANTINOS FOKIANOS 1 INTRODUCTION 337 2 INTEGER AUTOREGRESSIVE
PROCESSES AND INFERENCE 339 2.1 INTEGER AUTOREGRESSIVE PROCESSES 339 2.2
CONDITIONAL LEAST SQUARES INFERENCE 340 3 PENALIZED CONDITIONAL LEAST
SQUARES INFERENCE .341 4 EXAMPLES 343 4.1 SIMULATIONS 344 4.2 DATA
EXAMPLE 346 5 DISCUSSION 349 REFERENCES 350 APPENDIX 351 BAYESIAN
INFERENCE FOR A PERIODIC STOCHASTIC VOLATILITY MODEL OF INTRADAY
ELECTRICITY PRICES 353 MICHAEL STANLEY SMITH 1 INTRODUCTION 353 2
PERIODIC AUTOREGRESSIONS 355 3 PERIODIC STOCHASTIC VOLATILITY MODEL 356
3.1 THE MODEL 356 3.2 MATRIX PARAMETERISATIONS 357 3.3 THE AUGMENTED
LIKELIHOOD 358 3.4 PRIORS 358 4 BAYESIAN POSTERIOR INFERENCE 359 4.1
SAMPLING SCHEME 359 4.2 POSTERIOR INFERENCE AND FORECASTS 360 5 INTRADAY
ELECTRICITY PRICES 361 5.1 THE AUSTRALIAN ELECTRICITY MARKET AND SPOT
PRICE 361 5.2 EMPIRICAL ANALYSIS OF NSW SPOT PRICE 365 6 DISCUSSION 368
REFERENCES 370 XVI CONTENTS ONLINE CHANGE-POINT DETECTION IN CATEGORICAL
TIME SERIES 377 MICHAEL HOEHLE 1 INTRODUCTION 377 2 MODELING CATEGORICAL
TIME SERIES 378 2.1 BINOMIAL AND BETA-BINOMIAL DATA 379 2.2 NOMINAL DATA
380 2.3 ORDINAL DATA 380 2.4 PAIRED COMPARISONS 381 3 PROSPECTIVE CUSUM
CHANGEPOINT DETECTION 382 3.1 BINOMIAL AND BETA-BINOMIAL CUSUM 383 3.2
MULTINOMIAL CUSUM 384 3.3 ORDINAL AND BRADLEY-TERRY CUSUM 386 3.4
RUN-LENGTH OF TIME VARYING CATEGORICAL CUSUM 386 4 APPLICATIONS 388 4.1
MEAT INSPECTION 388 4.2 AGEGROUPS OF VARICELLA CASES 389 4.3 STRENGTH OF
BUNDESLIGA TEAMS 392 5 DISCUSSION 394 REFERENCES 395 MULTIPLE LINEAR
PANEL REGRESSION WITH MULTIPLICATIVE RANDOM NOISE . 399 HANS
SCHNEEWEISS AND GERD RONNING 1 INTRODUCTION 399 2 THE MODEL 401 3 THE
NAIVE ESTIMATOR AND ITS BIAS 402 4 CORRECTED ESTIMATOR 405 5 RESIDUAL
VARIANCE AND INTERCEPT 407 6 ASYMPTOTIC COVARIANCE MATRIX 408 7
SIMULATION 409 8 CONCLUSION 412 REFERENCES 413 A NOTE ON USING MULTIPLE
SINGULAR VALUE DECOMPOSITIONS TO CLUSTER COMPLEX INTRACELLULAR CALCIUM
ION SIGNALS 419 JOSUE G. MARTINEZ, JIANHUA Z. HUANG AND RAYMOND J.
CARROLL 1 INTRODUCTION 419 2 EXPERIMENT 421 2.1 TREATMENTS 421 2.2
IMAGING 422 3 CONTENTS XVII ON THE SELF-REGULARIZATION PROPERTY OF THE
EM ALGORITHM FOR POISSON INVERSE PROBLEMS 431 AXEL MUNK AND MIHAELA
PRICOP 1 INTRODUCTION 431 1.1 THE EM ALGORITHM FOR POISSON INVERSE
PROBLEMS 431 1.2 CONVERGENCE PROPERTIES 435 1.3 SELF-REGULARIZATION 436
1.4 STOPPING RULES 436 2 SCALING PROPERTIES OF THE EM ALGORITHM 439 3
THE EFFECT OF THE INITIAL GUESS 443 REFERENCES 446 SEQUENTIAL DESIGN OF
COMPUTER EXPERIMENTS FOR CONSTRAINED OPTIMIZATION 449 BRIAN J. WILLIAMS,
THOMAS J. SANTNER, WILLIAM I. NOTZ AND JEFFREY S. LEHMAN 1 INTRODUCTION
450 2 MODELING 451 3 A MINIMIZATION ALGORITHM 453 3.1 THE VIPER
ALGORITHM 454 3.2 IMPLEMENTATION DETAILS 455 4 AN AUTOREGRESSIVE MODEL
AND EXAMPLE 458 4.1 A BIVARIATE GAUSSIAN STOCHASTIC PROCESS MODEL 458
4.2 AN EXAMPLE WITH SIX INPUT VARIABLES 459 4.3 IMPLEMENTATION
RECOMMENDATIONS 462 4.4 OTHER CONCLUSIONS 465 5 DISCUSSION 466
REFERENCES 471 |
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| indexdate | 2025-01-11T13:44:42Z |
| institution | BVB |
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| language | English |
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| spelling | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir Thomas Kneib ... ed. Berlin [u.a.] Physica-Verl. 2010 XXIV, 472 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Statistisches Modell (DE-588)4121722-6 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content (DE-588)4016928-5 Festschrift gnd-content Statistisches Modell (DE-588)4121722-6 s DE-604 Kneib, Thomas 1976- (DE-588)131555332 edt Fahrmeir, Ludwig 1945- (DE-588)120635682 hnr Erscheint auch als Online-Ausgabe 978-3-7908-2413-1 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020195344&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir Statistisches Modell (DE-588)4121722-6 gnd |
| subject_GND | (DE-588)4121722-6 (DE-588)4143413-4 (DE-588)4016928-5 |
| title | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir |
| title_auth | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir |
| title_exact_search | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir |
| title_full | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir Thomas Kneib ... ed. |
| title_fullStr | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir Thomas Kneib ... ed. |
| title_full_unstemmed | Statistical modelling and regression structures Festschrift in honour of Ludwig Fahrmeir Thomas Kneib ... ed. |
| title_short | Statistical modelling and regression structures |
| title_sort | statistical modelling and regression structures festschrift in honour of ludwig fahrmeir |
| title_sub | Festschrift in honour of Ludwig Fahrmeir |
| topic | Statistisches Modell (DE-588)4121722-6 gnd |
| topic_facet | Statistisches Modell Aufsatzsammlung Festschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020195344&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT kneibthomas statisticalmodellingandregressionstructuresfestschriftinhonourofludwigfahrmeir AT fahrmeirludwig statisticalmodellingandregressionstructuresfestschriftinhonourofludwigfahrmeir |