P
ROGRAMME AND
A
BSTRACTS
9th International Conference on
Computational and Financial Econometrics (CFE 2015)
http://www.cfenetwork.org/CFE2015
and
8th International Conference of the
ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on
Computational and Methodological Statistics (CMStatistics 2015)
http://www.cmstatistics.org/CMStatistics2015
Senate House & Birkbeck University of London, UK
12 – 14 December 2015
Econometrics and Statistics
http://CMStatistics.org
http://CFEnetwork.org
c
ISBN 978-9963-2227-0-4
c
⃝2015 - CFE and CMStatistics networks
Technical Editors: Angela Blanco-Fernandez and Gil Gonzalez-Rodriguez.
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted, in any other form or by any means without the prior permission from the publisher.
Contents
General Information I
Committees . . . III Welcome . . . IV CMStatistics: ERCIM Working Group on Computational and Methodological Statistics . . . V CFEnetwork: Computational and Financial Econometrics . . . V Scientific programme . . . VI Tutorials, Meetings and Social events . . . VII Venue, Registration, Presentation instructions, Posters and Internet connection . . . VII Lecture rooms, Information messages and Exhibitors . . . VIII Map of the venue and nearby area . . . IX Publications outlets of the journals EcoSta and CSDA and Call for papers . . . X
Keynote Talks 1
Keynote talk 1 (Tim Bollerslev, Duke University, United States) Saturday 12.12.2015 at 08:40 - 09:30
Realized volatility based forecasting models: Exploiting the errors . . . 1
Keynote talk 2 (Richard Samworth, University of Cambridge, United Kingdom) Saturday 12.12.2015 at 10:05 - 10:55 Random projection ensemble classification . . . 1
Keynote talk 3 (George Kapetanios, Queen Mary University of London, United Kingdom) Sunday 13.12.2015 at 18:30 - 19:20 Estimation and Inference for random time varying coefficient models . . . 1
Keynote talk 4 (Jianqing Fan, Princeton University, United States) Monday 14.12.2015 at 12:05 - 12:55 Distributed estimation and inference with statistical guarantees . . . 1
Keynote talk 5 (Peter Diggle, Lancaster University and University of Liverpool, United Kingdom) Monday 14.12.2015 at 18:10 - 19:00 Model-based geostatistics for prevalence mapping in low-resource settings . . . 1
Parallel Sessions 2 Parallel Session B – CFE (Saturday 12.12.2015 at 09:40 - 10:55) 2 CO416: ANALYSIS OF HIGH-DIMENSIONAL TIME SERIESI (Room: Chancellor’s Hall) . . . 2
CO623: STATE SPACE MODELS AND COINTEGRATION(Room: Bloomsbury) . . . 2
CO596: TEMPORAL AND SPATIAL ECONOMETRIC MODELLING AND TESTING(Room: Montague) . . . 3
CO524: MODELING COMMODITY PRICES AND VOLATILITY(Room: Athlone) . . . 3
CO464: EARLY WARNING SYSTEM AND SYSTEMIC RISK INDICATORSI (Room: Woburn) . . . 3
CO392: GARCHINNOVATIONS(Room: Senate) . . . 4
CO528: FUNDS PERFORMANCE MEASUREMENT(Room: Holden) . . . 4
CO496: TIME SERIES(Room: SH349) . . . 5
CO420: ROBUST METHODS(Room: Jessel) . . . 5
CO538: MACROECONOMIC ANALYSIS(Room: Gordon) . . . 5
CO418: CO-MOVEMENTS IN MACRO AND FINANCE TIME SERIES(Room: Court) . . . 6
CO424: TECHNICAL ANALYSIS AND ADAPTIVE MARKETS(Room: Torrington) . . . 6
CG577: CONTRIBUTIONS ON NONSTATIONARY TIME SERIES AND PANELS(Room: Bedford) . . . 7
Parallel Session D – CFE-CMStatistics (Saturday 12.12.2015 at 11:25 - 13:05) 8 CI016: SPECIAL SESSION ONBAYESIAN METHODS IN ECONOMICS AND FINANCE(Room: Beveridge Hall) . . . 8
CO590: EMPIRICAL MODEL DISCOVERY(Room: Senate) . . . 8
CO568: MODELLING RISK(Room: Holden) . . . 9
CO436: TIME-SERIES ECONOMETRICS(Room: Jessel) . . . 9
CO578: MEASUREMENT OF MARKET SPILLOVERS(Room: SH349) . . . 10
CO506: MODELLING VOLATILITY(Room: Athlone) . . . 11
CO566: NONCAUSAL AND NONGAUSSIAN TIME SERIES MODELS(Room: Chancellor’s Hall) . . . 11
CO490: THE ECONOMETRICS OF CLIMATE CHANGE(Room: Bedford) . . . 12
CO410: FINANCIAL REGULATION(Room: Bloomsbury) . . . 12
CO542: FINANCE AND JOBS IN DYNAMIC MACRO MODELS(Room: Torrington) . . . 13
CO570: SPARSE MODELLING,SHRINKAGE AND REGULARIZATION(Room: Court) . . . 14
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CO625: CREDIT RISK MODELLING(Room: Montague) . . . 14
CO556: ASSET PRICE BUBBLES(Room: Gordon) . . . 15
CO434: GOODNESS-OF-FIT,MULTIPLE PREDICTORS AND MULTIVARIATE MODELS(Room: G21A) . . . 15
CO454: NOWCASTING AND FORECASTING UNDER UNCERTAINTYI (Room: Woburn) . . . 16
EI010: SPECIAL SESSION ON ROBUSTNESS FOR FUNCTIONAL AND COMPLEX DATA(Room: CLO B01) . . . 16
EO182: STATISTICS FOR COSMOLOGICAL DATA(Room: MAL 540) . . . 17
EO138: CLUSTERING MIXED DATA(Room: MAL 421) . . . 17
EO136: METHODS FOR THE ANALYSIS OF SEMI-COMPETING RISKS DATA(Room: MAL B33) . . . 18
EO288: RECENT DEVELOPMENT ON SINGLE INDEX MODELS(Room: CLO 203) . . . 19
EO184: OBJECT ORIENTED DATA ANALYSISI (Room: CLO 101) . . . 19
EO635: BAYESIAN SEMI-AND NONPARAMETRIC MODELLINGI (Room: MAL B20) . . . 20
EO206: STOCHASTIC PROCESSES WITH APPLICATIONS(Room: MAL B35) . . . 20
EO322: METHODOLOGY AND APPLICATIONS OF LATENT VARIABLE MODELS(Room: MAL 415) . . . 21
EO040: TOPICS IN DIRECTIONAL STATISTICS(Room: CLO 102) . . . 21
EO294: STATISTICAL EVALUATION OF MEDICAL DIAGNOSTIC TESTS(Room: CLO 306) . . . 22
EO180: INFERENCE IN MULTIPLE AND MATRIX GRAPHICAL MODELS(Room: MAL G15) . . . 23
EO060: APPLICATIONS OF EMPIRICAL MEASURES AND EMPIRICAL PROCESSES(Room: MAL B29) . . . 23
EO312: RECENT DEVELOPMENTS IN OPTIMAL DESIGN OF EXPERIMENTS(Room: CLO 204) . . . 24
EO096: DEPENDENCE MODELS AND COPULASI (Room: MAL B34) . . . 24
EO314: HIGH DIMENSIONS AND SMALL SAMPLE SIZES IN MULTIVARIATE INFERENCE(Room: MAL 414) . . . 25
EO222: STATISTICAL METHODS FOR BIG DATA AND ANTIFRAUD ANALYSIS(Room: MAL B36) . . . 25
EO058: CHANGE POINT ANALYSIS(Room: MAL 402) . . . 26
EC039: CONTRIBUTIONS ON REGRESSION ANALYSIS(Room: MAL 539) . . . 26
Parallel Session E – CFE-CMStatistics (Saturday 12.12.2015 at 14:25 - 16:05) 28 CO494: FORECASTING IN CENTRAL BANKS(Room: MAL B33) . . . 28
CO390: MULTIVARIATEGARCHAND DYNAMIC CORRELATION MODELS(Room: MAL B34) . . . 28
CO637: NOWCASTING AND FORECASTING UNDER UNCERTAINTYII (Room: MAL G15) . . . 29
CO478: VOLATILITY MODELING AND CORRELATION IN FINANCIAL MARKETS(Room: MAL 421) . . . 29
CO550: PORTFOLIO SELECTION AND ASSET PRICING AND MODELLING(Room: MAL 402) . . . 30
CO442: CORPORATE FINANCE(Room: MAL B29) . . . 30
CO530: TOPICS IN TIME SERIES AND PANEL DATA ECONOMETRICS (Room: MAL 414) . . . 31
CO588: NEWBAYESIAN METHODS AND ECONOMETRIC APPLICATIONS(Room: MAL B20) . . . 32
CO444: APPLIED FINANCIAL ECONOMETRICS(Room: MAL B36) . . . 32
CO514: ECONOMETRIC CHALLENGES IN RISK MANAGEMENT(Room: MAL B35) . . . 33
CG017: CONTRIBUTIONS ONBAYESIAN METHODS IN ECONOMICS AND FINANCE(Room: MAL 539) . . . 33
CG375: CONTRIBUTIONS ON NON-STARIONARITY AND NON-LINEARITY(Room: MAL 415) . . . 34
EO160: BAYESIAN ANALYSIS OF MISSING DATA AND LONGITUDINAL DATA(Room: Court) . . . 35
EO100: ADVANCES IN ROBUST DATA ANALYSIS(Room: Senate) . . . 35
EO048: STATISTICS FOR GENOMICS(Room: CLO 306) . . . 36
EO645: DEPENDENCE MODELS AND COPULASII (Room: Chancellor’s Hall) . . . 37
EO168: RECENT ADVANCES IN STATISTICAL MODELING AND COMPUTATION(Room: CLO 203) . . . 37
EO140: MULTIPLE TESTSI (Room: Bedford) . . . 38
EO204: BLIND SOURCE SEPARATION MODELS FOR TIME SERIES AND FUNCTIONAL DATA(Room: CLO 101) . . . 38
EO082: MULTI-STATE MODELS(Room: Woburn) . . . 39
EO126: MODELLING AND COMPUTATION IN STATISTICS OF EXTREMES(Room: Montague) . . . 40
EO342: RECENT ADVANCES IN FUNCTIONAL DATA ANALYSIS ANDBAYESIAN STATISTICS(Room: CLO 102) . . . 40
EO336: GENERALIZED LINEAR MODELS AND BEYOND(Room: Torrington) . . . 41
EO196: THEORY AND APPLICATIONS OF FUNCTIONAL DATA ANALYSIS(Room: CLO B01) . . . 41
EO174: OPTIMAL DESIGNS IN NON-STANDARD SITUATIONS(Room: CLO 204) . . . 42
EO208: HIGH-DIMENSIONAL STATISTICS(Room: Beveridge Hall) . . . 43
EO142: NONPARAMETRICBAYESIAN METHODS AND INVERSE PROBLEMS(Room: Holden) . . . 43
EO326: STATISTICS FOR FUZZY-OR SET-VALUED DATAI (Room: Athlone) . . . 44
EO192: APPLICATIONS OF MIXTURE MODELS(Room: Jessel) . . . 44
EO276: GRAPHICALMARKOV MODELS AND TOTALLY POSITIVE DEPENDENCES(Room: Bloomsbury) . . . 45
EC038: CONTRIBUTIONS ON SEMI-AND NON-PARAMETRIC STATISTICS(Room: Gordon) . . . 45
EG123: CONTRIBUTIONS ON NETWORKS(Room: G21A) . . . 46
EG099: CONTRIBUTIONS ON INDEPENDENCE AND DISTANCE-BASED METHODS(Room: SH349) . . . 46
EP653: POSTERSESSIONI (Room: Macmillan Hall and Crush Hall ) . . . 47
Parallel Session F – CFE-CMStatistics (Saturday 12.12.2015 at 16:35 - 18:40) 51 CI018: SPECIAL SESSION ON BOOTSTRAP INFERENCE(Room: Senate) . . . 51
CO438: LARGE DIMENSIONAL PANEL MODELS(Room: G21A) . . . 51
CO456: INFLATION ANALYSIS AND FORECASTING(Room: Woburn) . . . 52
CO422: ECONOMETRICS OF ART MARKETS(Room: Bedford) . . . 52
CO394: COMMODITY MARKETS: PRICING AND TRADING(Room: Torrington) . . . 53
CO548: BANKS AND THE MACROECONOMY IN THE CONTEXT OF STRESS TESTING(Room: Jessel) . . . 54
CO388: STRUCTURE IN MULTIVARIATE AND HIGH DIMENSIONAL TIME SERIES(Room: Chancellor’s Hall) . . . 55
CO484: FISCAL POLICY(Room: Athlone) . . . 56
CO508: REGIME CHANGE MODELING IN ECONOMICS AND FINANCEI (Room: Court) . . . 56
CO532: FINANCIAL RISK(Room: Bloomsbury) . . . 57
CO402: QUANTIFYING SOCIAL MEDIA IMPACT ON FINANCIAL DYNAMICS(Room: Holden) . . . 58
CO482: FINANCIAL FORECASTING(Room: Montague) . . . 59
CO362: RECENT DEVELOPMENTS IN TIME VARYING MODELLING(Room: SH349) . . . 59
CO348: TIME-FREQUENCY ANALYSIS OF ECONOMIC AND FINANCIAL DATA(Room: Gordon) . . . 60
EI008: SPECIAL SESSION ON STATISTICS FOR FUNCTIONAL DATA(Room: CLO B01) . . . 61
EO046: RESAMPLING PROCEDURES FOR DEPENDENT DATA(Room: CLO 101) . . . 61
EO176: HIGH-PERFORMANCE COMPUTING FOR STATISTICS, MLAND BIG DATA(Room: MAL B33) . . . 62
EO098: STATISTICAL MODELLING(Room: MAL 421) . . . 63
EO092: SPATIAL EXTREMES AND MAX-STABLE PROCESSES(Room: MAL B35) . . . 63
EO076: MACHINE LEARNING,APPROXIMATION AND ROBUSTNESS(Room: MAL B36) . . . 64
EO070: MODEL ASESSMENT(Room: MAL 414) . . . 65
EO234: RPACKAGES FOR MULTIVARIATE OUTLIER DETECTION(Room: MAL B34) . . . 65
EO150: CONVEX OPTIMIZATION IN STATISTICS(Room: MAL B29) . . . 66
EO210: MODELING AND STATISTICAL INFERENCE OF RECURRENT EVENTS(Room: MAL B20) . . . 67
EO116: ASYMPTOTIC PROPERTIES IN NONPARAMETRIC PROBLEMS(Room: CLO 203) . . . 67
EO144: SPATIAL AND SPATIO-TEMPORAL PROCESSES AND THEIR APPLICATIONS(Room: MAL G15) . . . 68
EO452: COMPUTATIONAL APPROACHES IN FINANCIAL ECONOMICS(Room: MAL B30) . . . 69
EO266: STATISTICAL METHODS FOR ACTUARIAL SCIENCES AND FINANCE(Room: MAL 415) . . . 69
EO302: DESIGNS FOR NONLINEAR MIXED EFFECT MODELS(Room: CLO 204) . . . 70
EO166: RECENT DEVELOPMENT OF EXPERIMENTAL DESIGNS(Room: CLO 306) . . . 71
EG263: CONTRIBUTIONS ON CENSORED DATA(Room: MAL 540) . . . 72
EG041: CONTRIBUTIONS IN COMPUTATIONAL AND NUMERICAL STATISTICS(Room: CLO 102) . . . 72
EG011: CONTRIBUTIONS ONBAYESIAN COMPUTATIONS(Room: MAL 402) . . . 73
EC036: CONTRIBUTIONS IN APPLIED STATISTICS AND DATA ANALYSIS(Room: MAL 539) . . . 74
Parallel Session G – CFE-CMStatistics (Sunday 13.12.2015 at 08:45 - 10:25) 76 CO510: ECONOMETRIC ANALYSES OF SPILLOVERS AND LIQUIDITY(Room: MAL B29) . . . 76
CO639: NOWCASTING AND FORECASTING UNDER UNCERTAINTYIII (Room: MAL G15) . . . 76
CO544: MODELLING AND COMPUTATION IN MACRO-ECONOMETRICS(Room: MAL B33) . . . 77
CO468: MACROECONOMICS,ASSET PRICING,AND ROBUSTNESS(Room: MAL B34) . . . 77
CO446: BAYESIAN NONPARAMETRIC ECONOMETRICS(Room: MAL B20) . . . 78
CO512: TOPICS IN FINANCIAL ECONOMETRICS(Room: MAL B30) . . . 79
CO470: QUANTITATIVE ASSET MANAGEMENT(Room: MAL 402) . . . 79
CO502: PANEL DATA MODELS WITH COMMON FACTORS: THEORY AND APPLICATIONS(Room: MAL 415) . . . 80
CO354: MEASURING AND FORECASTING DEFAULT RISK(Room: MAL B35) . . . 80
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CO518: FINANCIAL VOLATILITY AND COVARIANCE MODELLING(Room: MAL B36) . . . 81
CO370: MEASURING FINANCIAL RISK(Room: MAL 421) . . . 82
CO352: NONLINEAR MODELLING OF FINANCIAL TIME SERIES(Room: MAL 414) . . . 82
CG469: CONTRIBUTIONS INDSGEMODELLING(Room: MAL 541) . . . 83
CG499: CONTRIBUTIONS ON FINANCIAL TIME SERIES AND RISK PREMIA(Room: MAL 540) . . . 83
CG551: CONTRIBUTIONS ON PORTFOLIO SELECTION(Room: MAL 539) . . . 84
EO214: WAVELET METHODS IN STATISTICS(Room: Gordon) . . . 84
EO072: THEORETICAL FOUNDATION OF BIG DATA(Room: SH349) . . . 85
EO152: ESTIMATION AND INFERENCE IN HIGH DIMENSIONAL AND MIXTURE COPULAS(Room: Chancellor’s Hall) . . . 86
EO615: ADVANCED COMPUTATIONAL METHODS FOR COMPLEX DATA(Room: CLO 102) . . . 86
EO238: FUNCTIONAL AND OBJECT DATA WITH COMPLEX DEPENDENCIES(Room: CLO B01) . . . 87
EO290: ADVANCED METHODS FOR NEUROIMAGING DATA ANALYSIS(Room: CLO 203) . . . 87
EO308: TOPICS ON DISTANCE CORRELATION(Room: Montague) . . . 88
EO074: ADVANCES INBAYESIAN NONPARAMETRIC METHODS(Room: Court) . . . 88
EO170: BAYESIAN METHODS IN OFFICIAL STATISTICS(Room: Jessel) . . . 89
EO114: ADVANCES IN LATENT VARIABLE MODELS(Room: Senate) . . . 90
EO130: ROBUSTNESS,BIAS REDUCTION,MULTIVARIATE EXTREME(Room: Bedford) . . . 90
EO226: DEPTH AND FUNCTIONAL DATA ANALYSIS(Room: CLO 101) . . . 91
EO110: MODEL SELECTION WITH APPLICATIONS IN GENETICS(Room: CLO 306) . . . 91
EO080: MULTIVARIATE SURVIVAL MODELS(Room: Woburn) . . . 92
EO340: DESIGN AND ANALYSIS OF CLINICAL TRIALS(Room: CLO 204) . . . 93
EO112: RECENT ADVANCES IN TIME SERIES ANALYSIS(Room: Torrington) . . . 93
EO611: STATISTICAL METHODS FOR IMPERFECT DATA(Room: Athlone) . . . 94
EO328: GRAPHICAL MODELS AND CAUSALITY(Room: Bloomsbury) . . . 94
EO122: METHODS AND MODELS FOR SOCIAL NETWORKS DATA(Room: Holden) . . . 95
EO598: MATRIX COMPUTATIONS AND PARALLELISM IN STATISTICS(Room: G21A) . . . 96
Parallel Session H – CFE-CMStatistics (Sunday 13.12.2015 at 10:55 - 13:00) 97 CI022: SPECIAL SESSION ON MODELLING HETEROSKEDASTICITY(Room: Beveridge Hall) . . . 97
CO584: EMPIRICAL MACROECONOMICS(Room: Holden) . . . 97
CO641: MODELLING AND FORECASTING CYCLICAL FLUCTUATIONSII (Room: Woburn) . . . 98
CO382: NEW DEVELOPMENTS IN FINANCIAL TIME SERIES ANALYSIS(Room: Chancellor’s Hall) . . . 99
CO364: MEASURING SYSTEMIC RISK(Room: Court) . . . 99
CO576: NONSTATIONARY TIME SERIES AND PANELS(Room: Bedford) . . . 100
CO408: MONITORING AND TRACKING DEPENDENCE(Room: SH349) . . . 101
CO376: QUANTILE REGRESSION IN FINANCE AND ECONOMICS(Room: Bloomsbury) . . . 102
CO504: REGIME SWITCHING,FILTERING,AND PORTFOLIO OPTIMIZATION(Room: Torrington) . . . 102
CO358: NUMERICAL METHODS AND ESTIMATION OFDSGEMODELS(Room: Gordon) . . . 103
CO360: ESTIMATION AND INFERENCE IN LONG MEMORY PROCESSES(Room: Montague) . . . 104
CO448: MACROECONOMIC UNCERTAINTY AND POLICY(Room: Jessel) . . . 104
CO516: RISK AND VOLATILITY MODELLING(Room: Athlone) . . . 105
CO286: FINANCIAL TIME SERIES(Room: G21A) . . . 106
CO386: INDIRECT INFERENCE AND RELATED METHODS(Room: Senate) . . . 106
CP002: POSTERSESSION(Room: Macmillan Hall and Crush Hall ) . . . 107
EI012: SPECIAL SESSION ON OPTIMAL EXPERIMENTAL DESIGN(Room: CLO B01) . . . 109
EO246: MULTIVARIATE SURVIVAL DATA WITH LATENT VARIABLES(Room: MAL 421) . . . 109
EO278: INFERENCE FOR STOCHASTIC PROCESSES(Room: MAL B29) . . . 110
EO216: CHANGE POINT ANALYSIS(Room: MAL 402) . . . 111
EO609: MIXTURE MODELS FOR NON-VECTORIAL DATA(Room: MAL B30) . . . 112
EO102: MULTIVARIATE EXTREMES(Room: MAL B35) . . . 112
EO108: OUTLIERS AND ROBUSTNESS IN TIME SERIES(Room: MAL B36) . . . 113
EO232: ADVANCES IN SURVIVAL AND RELIABILITY(Room: MAL B20) . . . 114
EO228: HIGH-DIMENSIONAL PEAKS OVER THRESHOLDS METHODS(Room: MAL B33) . . . 115
EO274: QUANTILE REGRESSION IN HIGH DIMENSION(Room: MAL 541) . . . 115
EO254: HEALTHECONOMICS(Room: MAL 540) . . . 116
EO042: RECENT ADVANCES ON FUNCTIONAL DATA ANALYSIS AND APPLICATIONS(Room: CLO 102) . . . 117
EO338: STATISTICAL BOOSTING(Room: MAL 415) . . . 117
EO186: AUTOMATIC BANDWIDTH SELECTION FOR KERNEL ESTIMATORS(Room: MAL 414) . . . 118
EO054: MULTIVARIATE ANALYSIS(Room: CLO 203) . . . 119
EO256: ROBUST STATISTICS INR (Room: MAL B34) . . . 120
EO607: STATISTICAL ASPECTS OF TOPOLOGICAL DATA ANALYSIS(Room: CLO 306) . . . 120
EO202: APPLICATIONS OF FUNCTIONAL DATA ANALYSIS(Room: CLO 101) . . . 121
EO078: INFERENCE FOR LARGE MATRICES WITH MODERN APPLICATIONS(Room: MAL G15) . . . 122
EG015: CONTRIBUTIONS IN TIME SERIES AND TIME-VARYING COEFFICIENTS(Room: CLO 204) . . . 122
EG013: CONTRIBUTIONS ON DEPENDENCE MODELLING(Room: MAL 539) . . . 123
Parallel Session I – CFE-CMStatistics (Sunday 13.12.2015 at 14:30 - 16:10) 125 CI020: SPECIAL SESSION ON ADVANCES IN DYNAMIC FACTOR ANALYSIS(Room: Beveridge Hall) . . . 125
CO536: FINANCIAL CONDITIONS INDICES(Room: Bedford) . . . 125
CO480: ADVANCES IN FINANCIAL FORECASTING(Room: SH349) . . . 126
CO426: COMMON FEATURES IN MACROECONOMICS AND FINANCE(Room: Holden) . . . 126
CO384: MULTIVARIATE METHODS FOR ECONOMIC AND FINANCIAL TIME SERIES(Room: Senate) . . . 127
CO380: BAYESIAN NONLINEAR ECONOMETRICS(Room: Court) . . . 127
CO396: WAVELET METHODS IN ECONOMICS(Room: Gordon) . . . 128
CO500: VOLATILITY MODELS(Room: Torrington) . . . 128
CO476: EMPIRICAL MACRO-FINANCE(Room: Jessel) . . . 129
CO522: TOPICS IN MULTIPLE TIME SERIES ANALYSIS(Room: Montague) . . . 130
CO368: BOOTSTRAP METHODS FOR TIME SERIES(Room: Chancellor’s Hall) . . . 130
CO356: MODELLING AND FORECASTING TEMPORAL DATA(Room: G21A) . . . 131
CO586: VOLATILITY MODELS AND THEIR APPLICATIONS(Room: Woburn) . . . 131
CO558: BEHAVIOURAL AND EMOTIONAL FINANCE: THEORY AND EVIDENCEI (Room: Bloomsbury) . . . 132
CC025: CONTRIBUTIONS IN PANEL DATA(Room: Athlone) . . . 133
EO132: STATISTICS IN IMAGING(Room: CLO 204) . . . 133
EO220: TEXT MINING,NETWORK DATA AND MIXTURE MODELING(Room: MAL 539) . . . 134
EO647: DEPENDENCE MODELS AND COPULASIII (Room: MAL B34) . . . 134
EO258: ROBUST METHODS(Room: MAL B36) . . . 135
EO272: MULTIVARIATEANALYSIS AND CHANGE-POINT DETECTION(Room: MAL 402) . . . 136
EO084: MULTIPLE TESTSII (Room: MAL B35) . . . 136
EO324: ANALYSIS OF COMPLEX TIME SERIES DATA(Room: MAL B30) . . . 137
EO198: IN-SAMPLEFORECASTING IN INSURANCE,LONGEVITY AND THE LABOUR MARKET(Room: CLO 203) . . . 137
EO318: STATISTICAL INFERENCE FOR BIOMEDICAL DATA(Room: CLO 306) . . . 138
EO088: FUNCTIONAL DATA AND RELATED TOPICS(Room: CLO B01) . . . 139
EO156: SPATIAL STATISTICS AND ECONOMETRICS(Room: MAL 421) . . . 139
EO128: STATISTICS IN FUNCTIONAL ANDHILBERT SPACES (Room: CLO 101) . . . 140
EO064: CALIBRATION OF MISSPECIFIEDBAYESIAN MODELS(Room: MAL B20) . . . 140
EO118: STATISTICAL REGULARIZATION(Room: MAL 414) . . . 141
EO212: CAUSAL DISCOVERY IN PRACTICE: ADVANCES AND CHALLENGES(Room: MAL G15) . . . 141
EO260: MODEL SELECTION AND COMPARISON IN HIGHLY-STRUCTURED SETTINGS(Room: MAL B33) . . . 142
EO264: DIRECTIONAL STATISTICS (Room: CLO 102) . . . 143
EG135: CONTRIBUTIONS IN EXTREME VALUES THEORY AND APPLICATIONS(Room: MAL 415) . . . 143
EC034: CONTRIBUTIONS IN METHODOLOGICAL STATISTICS(Room: MAL B29) . . . 144
EG055: CONTRIBUTIONS IN MULTIVARIATE ANALYSIS(Room: MAL 540) . . . 145
EC035: CONTRIBUTIONS IN COMPUTATIONAL STATISTICS(Room: MAL 541) . . . 145
Parallel Session J – CFE-CMStatistics (Sunday 13.12.2015 at 16:40 - 18:20) 147 CO458: MODELLING AND FORECASTING CYCLICAL FLUCTUATIONSI (Room: MAL G15) . . . 147
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CO562: RECENT ADVANCES INBAYESIAN COMPUTATIONAL METHODS(Room: MAL B20) . . . 147
CO554: MIXED-FREQUENCY TIME SERIES(Room: MAL 414) . . . 148
CO552: APPLIED ECONOMETRICS(Room: MAL B33) . . . 148
CO540: ECONOMETRICS OF DYNAMIC PORTFOLIOS AND RISK(Room: MAL B35) . . . 149
CO414: DENSITY REGRESSION,TREE MODELS,AND VARIABLE SELECTION(Room: MAL B34) . . . 150
CO657: REGIME CHANGE MODELING IN ECONOMICS AND FINANCEII (Room: MAL B36) . . . 150
CO374: NON-LINEAR TIME SERIES MODELS(Room: MAL 415) . . . 151
CO432: VOLATILITY MODELLING IN FINANCIAL MARKETS(Room: MAL B30) . . . 151
CG493: CONTRIBUTIONS ONVARAND EXTREME VALUE THEORY(Room: MAL 540) . . . 152
CG377: CONTRIBUTIONS ON QUANTILE REGRESSION IN FINANCE AND ECONOMICS(Room: MAL 421) . . . 152
CG349: CONTRIBUTIONS ON TIME-VAYING PARAMETERS ANDKALMAN FILTER(Room: MAL 539) . . . 153
CC030: CONSTRIBUTIONS IN FINANCIAL APPLICATIONS(Room: MAL 541) . . . 154
CG533: CONTRIBUTIONS ON SYSTEMIC RISK(Room: MAL B29) . . . 154
CG353: CONTRIBUTIONS ON TIME SERIES(Room: MAL 402) . . . 155
EI014: SPECIAL SESSION IN HONOR OFH. OJA’S65TH BIRTHDAY(Room: Beveridge Hall) . . . 155
EO252: STATISTICAL METHODS FOR COMPLEX LONGITUDINAL DATA(Room: Woburn) . . . 156
EO592: ADVANCES IN FUNCTIONAL DATA ANALYSIS(Room: CLO 101) . . . 156
EO124: TIME SERIES: NONPARAMETRICS AND EXTREMES(Room: Jessel) . . . 157
EO310: MODERN STATISTICAL REGRESSION(Room: Torrington) . . . 158
EO154: METHODS AND COMPUTATIONS FOR DEPENDENCE MODELLING(Room: Bedford) . . . 158
EO633: BAYESIAN SEMI-AND NONPARAMETRIC MODELLINGII (Room: Court) . . . 159
EO613: INFERENCE IN LATENT VARIABLE MODELS(Room: Senate) . . . 160
EO244: SEMI-AND NON-PARAMETRIC ESTIMATION OF FRONTIERS (Room: CLO 203) . . . 160
EO086: STATISTICAL ANALYSIS OF LONG-RANGE DEPENDENT DATA(Room: G21A) . . . 161
EO120: ON QUANTILES,EXPECTILES AND EXTREMILES(Room: Chancellor’s Hall) . . . 161
EO188: COMPUTATIONAL ASPECTS OF ESTIMATING STOCHASTIC PROCESSES(Room: Gordon) . . . 162
EO178: ROBUST STATISTICAL MODELLING(Room: Montague) . . . 163
EO268: ANALYSIS OF DATA FROM COMPLEX SURVEYS(Room: SH349) . . . 163
EO332: STATISTICS FOR FUZZY-OR SET-VALUED DATAII (Room: Athlone) . . . 164
EO230: SIMPSON’S PARADOX (Room: Bloomsbury) . . . 164
EO334: STRUCTURED DATA ANAYSIS(Room: CLO 306) . . . 165
EO200: NONPARAMETRIC FUNCTIONAL DATA ANALYSIS(Room: CLO B01) . . . 166
EG127: CONTRIBUTIONS ON LIKELIHOOD(Room: Holden) . . . 166
EG297: CONTRIBUTIONS ON MISSING DATA(Room: CLO 204) . . . 167
EG045: CONTRIBUTIONS ON COMPUTATIONAL METHODS FOR REGRESSION MODELS(Room: CLO 102) . . . 167
EP001: POSTERSESSIONII (Room: Macmillan Hall and Crush Hall ) . . . 168
Parallel Session L – CFE-CMStatistics (Monday 14.12.2015 at 08:30 - 10:10) 172 CO492: ANALYSIS OF EXTREMES AND DEPENDENCE(Room: MAL B20) . . . 172
CO498: FINANCIAL TIME SERIES AND RISK PREMIA(Room: MAL 633) . . . 172
CO462: EARLY WARNING SYSTEM AND SYSTEMIC RISK INDICATORSII (Room: MAL G15) . . . 173
CO350: FINANCIAL ECONOMETRICS(Room: MAL 539) . . . 173
CO400: BAYESIAN ECONOMETRICS(Room: MAL 532) . . . 174
CO372: FINANCIAL NETWORKS:SYSTEMIC COEVOLUTION OF FINANCIAL SYSTEMS(Room: MAL 402) . . . 174
CO412: MIXTURE MODELS,IDENTIFICATION,AND INDEPENDENT COMPONENTS(Room: MAL 541) . . . 175
CO582: RASTANEWSSPECIAL SESSION ON VOLATILITY AND TIME SERIES MODELING(Room: MAL 421) . . . 176
CO366: ENERGY AND MACROECONOMICS(Room: MAL 632) . . . 176
CG019: CONTRIBUTIONS ON BOOTSTRAP INFERENCE(Room: MAL 540) . . . 177
EO044: BIG DATA ANALYSIS: STATISTICAL METHODOLOGIES AND APPLICATIONS(Room: Holden) . . . 177
EO320: INFLUENCE AND ROBUSTNESS IN STATISTICAL MODELING(Room: Senate) . . . 178
EO164: BAYESIAN SEMI-AND NONPARAMETRIC MODELLINGIII (Room: Court) . . . 179
EO330: COPULA MODELS AND APPLICATIONS(Room: Chancellor’s Hall) . . . 179
EO066: NON-AND SEMI-PARAMETRIC FUNCTIONAL STATISTICSI (Room: CLO B01) . . . 180
EO162: ANALYSIS OF TOROIDAL AND CYLINDRICAL DATA(Room: Beveridge Hall) . . . 180
EO172: STATISTICAL INFERENCE AND APPLICATION IN FUNCTIONAL ANALYSIS(Room: Woburn) . . . 181
EO194: POPULATION MODELS: METHODS AND COMPUTATIONSI (Room: Bedford) . . . 182
EO621: COVARIANCE,VOLATILITY,AND EFFICIENT INFERENCE(Room: Gordon) . . . 182
EO292: DYNAMIC FACTOR MODELS AND SUFFICIENT DIMENSION REDUCTION(Room: Montague) . . . 183
EO629: MIXTURE MODEL AND VARIABLE SELECTION(Room: Jessel) . . . 183
EO056: SURVEY SAMPLING FOR FUNCTIONAL DATA AND/OR BIG DATA(Room: Bloomsbury) . . . 184
EO218: ANALYSIS OF SURVEY DATA FOR UNPLANNED DOMAIN(Room: SH349) . . . 184
EO106: ADVANCES IN FUZZY CLUSTERING(Room: Torrington) . . . 185
EG111: CONTRIBUTIONS ONLASSO(Room: Athlone) . . . 185
EG113: CONTRIBUTIONS IN TIME SERIES ANALYSISI (Room: G21A) . . . 186
Parallel Session M – CFE-CMStatistics (Monday 14.12.2015 at 10:40 - 11:55) 188 CO546: TIME-VARYING PARAMETERS(Room: Holden) . . . 188
CO440: ANALYSIS OF HIGH-DIMENSIONAL TIME SERIESII (Room: Senate) . . . 188
CO472: NONREGULAR PANEL DATA AND TIME SERIES MODELS(Room: SH349) . . . 189
CO643: EARLY WARNING SYSTEM AND SYSTEMIC RISK INDICATORSIII (Room: Athlone) . . . 189
CO488: FILTERS WAVELETS AND SIGNALS (Room: Gordon) . . . 190
CO486: SEQUENTIALMONTECARLO METHODS IN ECONOMETRICS(Room: Montague) . . . 190
CO474: DATA SCIENCE AND PLATFORM DESIGN(Room: Torrington) . . . 191
CO659: BEHAVIOURAL AND EMOTIONAL FINANCE: THEORY AND EVIDENCEII (Room: Bloomsbury) . . . 191
CO052: HIGH DIMENSIONAL MODELS AND NETWORKS IN MACROECONOMICS AND FINANCE(Room: Jessel) . . . 192
CG555: CONTRIBUTIONS ONGARCHMODELS(Room: Bedford) . . . 192
EO649: OBJECT ORIENTED DATA ANALYSISII (Room: Beveridge Hall) . . . 193
EO280: NETWORK INFERENCE(Room: MAL 633) . . . 193
EO344: SEMI-NON-PARAMETRIC STATISTICS WITH HIGH-DIMENSIONALITY(Room: MAL 539) . . . 193
EO270: STATISTICAL ANALYSIS OF TEXT(Room: MAL 541) . . . 194
EO296: ROBUSTNESS AND MISSING DATA(Room: MAL 532) . . . 194
EO619: RISK MANAGEMENT AND DEPENDENCE MODELLING(Room: Chancellor’s Hall) . . . 195
EO346: CLUSTERWISE METHODS(Room: MAL 540) . . . 195
EO250: COMBINATORIAL OPTIMIZATION FOR GRAPHICAL MODEL SELECTIONI (Room: MAL G15) . . . 196
EO298: RECENT DEVELOPMENTS INBAYESIAN QUANTILE REGRESSION(Room: Court) . . . 196
EO062: HIGH-DIMENSIONAL LATENT VARIABLE MODELS(Room: G21A) . . . 197
EO655: POPULATION MODELS: METHODS AND COMPUTATIONSII (Room: MAL 421) . . . 197
EO300: DEPENDENCE MODELS IN BIOSTATISTICS AND BIOINFORMATICS(Room: MAL 402) . . . 197
EO242: ADVANCED FUNCTIONAL DATA ANALYSIS(Room: CLO B01) . . . 198
EO284: RECENT DEVELOPMENTS IN SEMIPARAMETRIC ANALYSIS OF SURVIVAL DATA(Room: Woburn) . . . 198
Parallel Session O – CFE-CMStatistics (Monday 14.12.2015 at 14:30 - 15:50) 200 CG507: CONTRIBUTIONS ON VOLATILITY(Room: Woburn) . . . 200
CG287: CONTRIBUTIONS IN TIME SERIES AND APPLICATIONS(Room: Bedford) . . . 200
CG531: CONTRIBUTIONS IN PANEL DATA ECONOMETRICS (Room: Bloomsbury) . . . 201
CG485: CONTRIBUTIONS ON FISCAL POLICY(Room: Holden) . . . 201
CG597: CONTRIBUTIONS ON TEMPORAL AND SPATIAL ECONOMETRIC(Room: Chancellor’s Hall) . . . 202
CC027: CONTRIBUTIONS INBAYESIAN ECONOMETRICS(Room: Montague) . . . 203
CG569: CONTRIBUTIONS ON PRICING(Room: Athlone) . . . 204
CG359: CONTRIBUTIONS ON THE ESTIMATION OFDSGEMODELS(Room: SH349) . . . 204
CG553: CONTRIBUTIONS ON APPLIED ECONOMETRICS AND FINANCE(Room: Court) . . . 205
CG483: CONTRIBUTIONS ON FORECASTING (Room: Senate) . . . 206
CG395: CONTRIBUTIONS ON HIGH-FRECUENCY DATA(Room: Jessel) . . . 206
CG626: CONTRIBUTIONS ON CREDIT RISK MODELLING(Room: Torrington) . . . 207
CC029: CONTRIBUTIONS ON ASYMPTOTICS IN ECONOMETRICS(Room: Gordon) . . . 208
CC024: CONTRIBUTIONS IN FINANCIAL ECONOMETRICS(Room: G21A) . . . 208
c
EO306: ESTIMATION OF LARGE RANDOM MATRICES: THEORIES AND APPLICATIONS(Room: MAL 541) . . . 209
EO158: RECENT ADVANCES IN QUANTILE REGRESSION(Room: MAL 633) . . . 209
EO236: NETWORK STATISTICS(Room: MAL 421) . . . 210
EO104: COMPLEX DATA ANALYSIS: THEORY AND METHODS(Room: MAL B20) . . . 210
EO661: COMBINATORIAL OPTIMIZATION FOR GRAPHICAL MODEL SELECTIONII (Room: MAL G15) . . . 211
EO316: SHAPE-CONSTRAINED INFERENCE AND OTHER NON-REGULAR PROBLEMS(Room: MAL 632) . . . 211
EO190: ADVANCES IN MIXTURE MODELLING(Room: MAL 540) . . . 211
EO304: HIGH-DIMENSIONAL DATA ANALYSIS BEYOND LINEAR MODELS(Room: MAL 532) . . . 212
EG067: CONTRIBUTIONS ON COMPLEX DATA(Room: MAL 402) . . . 212
EC037: CONTRIBUTIONS ON LINEAR MODELS(Room: MAL 539) . . . 213
Parallel Session P – CFE-CMStatistics (Monday 14.12.2015 at 16:20 - 18:00) 214 CO460: SEASONAL ADJUSTMENT AND RECONCILIATION(Room: MAL G15) . . . 214
CG053: CONTRIBUTIONS ON BUSINESS CYCLE(Room: MAL 532) . . . 214
CG357: CONTRIBUTIONS ON EVALUATION OF FORECASTING(Room: MAL 632) . . . 215
CC028: CONTRIBUTIONS IN APPLIED ECONOMETRICS(Room: MAL 633) . . . 216
CG351: CONTRIBUTIONS ONMCMCANDBAYESIAN ECONOMETRICS(Room: MAL 421) . . . 217
CG021: CONTRIBUTIONS IN DYNAMIC FACTOR ANALYSIS(Room: MAL 541) . . . 217
CG457: CONTRIBUTIONS IN INFLATION ANALYSIS AND FORECASTING(Room: MAL 540) . . . 218
CC026: CONTRIBUTIONS IN TIME SERIES ECONOMETRICS(Room: MAL 402) . . . 219
CG023: CONTRIBUTIONS ON STOCHASTIC VOLATILITY (Room: MAL 539) . . . 220
EO262: NEW TRENDS IN SURVIVAL ANALYSIS(Room: Beveridge Hall) . . . 220
EO651: NON-AND SEMI-PARAMETRIC FUNCTIONAL STATISTICSII (Room: Woburn) . . . 221
EC032: CONTRIBUTIONS IN DIMENSION REDUCTION(Room: Bloomsbury) . . . 222
EG630: CONTRIBUTIONS ON VARIABLE SELECTION(Room: Holden) . . . 222
EG652: CONTRIBUTIONS ON STATISTICAL MODELLING FOR ECONOMICS AND FINANCE(Room: G21A) . . . 223
EG145: CONTRIBUTIONS ON SPATIAL AND SPATIO-TEMPORAL PROCESSES(Room: Gordon) . . . 224
EC033: CONTRIBUTIONS IN ROBUST STATISTICS(Room: Senate) . . . 225
EG347: CONTRIBUTIONS ON CLUSTERING AND CLASSIFICATION(Room: Jessel) . . . 226
EG169: CONTRIBUTIONS IN STATISTICAL MODELING AND COMPUTATION(Room: SH349) . . . 226
EG097: CONTRIBUTIONS ON DEPENDENCE MODELS AND COPULAS(Room: Chancellor’s Hall) . . . 227
EG009: CONTRIBUTIONS ON STATISTICS FOR FUNCTIONAL DATA(Room: Montague) . . . 228
EG325: CONTRIBUTIONS IN TIME SERIES ANALYSISII (Room: Bedford) . . . 229
EG159: CONTRIBUTIONS ON QUANTILE REGRESSION(Room: Torrington) . . . 229
EG233: CONTRIBUTIONS ON CONTROL AND RELIABILITY(Room: Athlone) . . . 230
EC031: CONTRIBUTIONS ONBAYESIAN METHODS(Room: Court) . . . 230
232
EO1330: Spatial clustering of time-series via mixtures of autoregressive models and Markov random fields for image analysis Presenter: Hien Nguyen, University of Queensland, Australia
Co-authors: Geoffrey McLachlan, Jeremy Ullmann, Andrew Janke
Time-series data arise in many medical and biological imaging scenarios. In such images, a time-series is obtained at each of a large number of spatially dependent data units (e.g. electrodes, pixels, or voxels). It is often interesting to organize these data units into clusters that are modeled by an underlying probabilistic process. A two-stage procedure is presented for this task. In Stage 1, a mixture of autoregressive (MoAR) model is used to marginally cluster the time series arising at each data unit. The MoAR model is fitted using maximum marginal likelihood (MML) estimation via an MM (minorizationmaximization) algorithm. In Stage 2, a Markov random field (MRF) model is used to induce a spatial dependency structure onto the Stage 1 clustering. The MRF model is also fitted using maximum pseudolikelihood (MPL) estimation via an MM algorithm. A simulation study is presented to demonstrate the performance of the two-stage procedure. An application to the segmentation of a zebrafish brain calcium image is presented as a demonstration of the methodology.
EC1246: Robust estimation for mixtures of skew data
Presenter: Francesca Greselin, University of Milano Bicocca, Italy
Co-authors: Luis Angel Garcia-Escudero, Agustin Mayo-Iscar, Geoffrey McLachlan
Recently, observed departures from the classical Gaussian mixture model in real datasets have led to the introduction of more flexible tools for modeling heterogeneous skew data. Among the latest proposals in the literature, we consider mixtures of skew normal, to incorporate asymmetry in components, as well as mixtures of t, to down-weight the contribution of extremal observations. Clearly, mixtures of skew t have widened the application of model based clustering and classification to great many real datasets, as they can adapt to both asymmetry and leptokurtosis in the grouped data. Unfortunately, when data contamination occurs far from the bulk of the data, or even between the groups, classical inference for these models is not reliable. Our proposal is to address robust estimation of mixtures of skew normal, to resist sparse outliers and even pointwise contamination that could arise in data collection. We introduce a constructive way to obtain a robust estimator for the mixture of skew normal model, by incorporating impartial trimming and constraints in the EM algorithm. At each E-step, a low percentage of less plausible observations, under the estimated model, is tentatively trimmed; at the M-step, constraints on the scatter matrices are employed to avoid singularities and reduce spurious maximizers. Some applications on artificial and real data show the effectiveness of our proposal, and the joint role of trimming and constraints to achieve robustness.
EO304 Room MAL 532 HIGH-DIMENSIONAL DATA ANALYSIS BEYOND LINEAR MODELS Chair: Junhui Wang
EO1303: Probability-enhanced sufficient dimension reduction for binary classification Presenter: Hao Zhang, University of Arizona, United States
Many sufficient dimension reduction (SDR) methods have been developed since the introduction of sliced inverse regression. For binary classifi-cation problems, SIR suffers the limitation of estimating at most one direction since only two slices are available. We propose a new and flexible probability-enhanced SDR method for binary classification problems using the weighted support vector machine (WSVM). The key idea is to slice the data based on conditional class probabilities of observations rather than their binary responses. We show that the central subspace based on the conditional class probability is the same as that based on the raw binary response, which justifies the proposed slicing scheme and assures no information loss. Furthermore, in order to implement the new slicing scheme, one does not need exact probability values since the only required information is the relative ordering of probability values. The new SDR bypasses the probability estimation and employs the WSVM to directly estimate the order of probability values, based on which the slicing is performed. The performance of the proposed probability-enhanced SDR scheme is evaluated by both simulated and real data examples.
EO0634: Sparse quadratic discriminant analysis Presenter: Chenlei Leng, Warwick, United Kingdom
A novel QUadratic Discriminant Analysis procedure called QUDA is proposed for analysing high-dimensional data. The proposed method is able to identify quadratic interactions of the variables for classification. Under appropriate sparsity assumptions, we show that QUDA works even when the dimensionality is exponentially high with respect to the sample size. We develop an efficient algorithm based on the alternating direction method of multipliers method (ADMM) for finding interactions along the way, which is much faster than its competitor in the literature. The competitive performance of QUDA is illustrated via extensive simulation studies and the analysis of real datasets.
EO0217: Sparse partially linear additive models Presenter: Jacob Bien, Cornell University, United States Co-authors: Yin Lou, Rich Caruana, Johannes Gehrke
The generalized partially linear additive model (GPLAM) is a flexible and interpretable approach to building predictive models. It combines features in an additive manner, allowing each to have either a linear or nonlinear effect on the response. However, the choice of which features to treat as linear or nonlinear is typically assumed known. Thus, to make a GPLAM a viable approach in situations in which little is known a priori about the features, one must overcome two primary model selection challenges: deciding which features to include in the model and determining which of these features to treat nonlinearly. We introduce the sparse partially linear additive model (SPLAM), which combines model fitting and both of these model selection challenges into a single convex optimization problem. SPLAM provides a bridge between the lasso and sparse additive models. Through a statistical oracle inequality and thorough simulation, we demonstrate that SPLAM can outperform other methods across a broad spectrum of statistical regimes, including the high-dimensional setting. We develop efficient algorithms that are applied to real data sets with half a million samples and over 45,000 features with excellent predictive performance.
EG067 Room MAL 402 CONTRIBUTIONS ON COMPLEX DATA Chair: Thaddeus Tarpey
EC1635: Rate of uniform consistency for a class of mode regression on functional stationary ergodic data Presenter: Mohamed Chaouch, United Arab Emirates University, United Arab Emirates
Co-authors: Naamane Laib, Djamal Louani
The aim is to study the asymptotic properties of a class of kernel conditional mode estimates whenever functional stationary ergodic data are considered. To be more precise, in the ergodic data setting, we consider a random element (X;Z) taking values in some semi-metric abstract space E × F. For a real function ϕ defined on the space F and x ∈ E, we consider the conditional mode of the real random variable ϕ(Z) given the event X = x. While estimating the conditional mode function, sayθϕ(x), using the well-known kernel estimator, we establish the strong consistency with
rate of this estimate uniformly over Vapnik-Chervonenkis classes of functionsϕ. Notice that the ergodic setting offers a more general framework than the usual mixing structure. Two applications to energy data are provided to illustrate some examples of the proposed approach in time series forecasting framework. The first one consists in forecasting the daily peak of electricity demand in France (measured in Giga-Watt). Whereas the second one deals with the short-term forecasting of the electrical energy (measured in Giga-Watt per Hour) that may be consumed over some time intervals that cover the peak demand.