Modeling and stochastic learning for forecasting in high dimensions:
Saved in:
| Format: | Electronic eBook |
|---|---|
| Language: | English |
| Published: |
Cham [u.a.]
Springer
2015
|
| Series: | Lecture Notes in Statistics
217 |
| Subjects: | |
| Online Access: | BTU01 FRO01 TUM01 UBM01 UBT01 UBW01 UPA01 Volltext Inhaltsverzeichnis Abstract |
| Physical Description: | 1 Online-Ressource (X, 339 S.) 105 illus., 49 illus. in color |
| ISBN: | 9783319187327 |
| ISSN: | 0930-0325 |
| DOI: | 10.1007/978-3-319-18732-7 |
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Record in the Search Index
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| adam_text | MODELING AND STOCHASTIC LEARNING FOR FORECASTING IN HIGH DIMENSIONS
/
: 2015
TABLE OF CONTENTS / INHALTSVERZEICHNIS
1 SHORT TERM LOAD FORECASTING IN THE INDUSTRY FOR ESTABLISHING
CONSUMPTION BASELINES: A FRENCH CASE
2 CONFIDENCE INTERVALS AND TESTS FOR HIGH-DIMENSIONAL MODELS: A COMPACT
REVIEW
3 MODELLING AND FORECASTING DAILY ELECTRICITY LOAD VIA CURVE LINEAR
REGRESSION
4 CONSTRUCTING GRAPHICAL MODELS VIA THE FOCUSED INFORMATION CRITERION
5 NONPARAMETRIC SHORT TERM FORECASTING ELECTRICITY CONSUMPTION WITH IBR
6 FORECASTING THE ELECTRICITY CONSUMPTION BY AGGREGATING EXPERTS
7 FLEXIBLE AND DYNAMIC MODELING OF DEPENDENCIES VIA COPULAS
8 OPERATIONAL AND ONLINE RESIDENTIAL BASELINE ESTIMATION
9 FORECASTING INTRA DAY LOAD CURVES USING SPARSE FUNCTIONAL REGRESSION
10 MODELLING AND PREDICTION OF TIME SERIES ARISING ON A GRAPH
11 GAM MODEL BASED LARGE SCALE ELECTRICAL LOAD SIMULATION FOR SMART
GRIDS
12 SPOT VOLATILITY ESTIMATION FOR HIGH-FREQUENCY DATA: ADAPTIVE
ESTIMATION IN PRACTICE
13 TIME SERIES PREDICTION VIA AGGREGATION: AN ORACLE BOUND INCLUDING
NUMERICAL COST
14 SPACE-TIME TRAJECTORIES OF WIND POWER GENERATION: PARAMETRIZED
PRECISION MATRICES UNDER A GAUSSIAN COPULA APPROACH
15 GAME-THEORETICALLY OPTIMAL RECONCILIATION OF CONTEMPORANEOUS
HIERARCHICAL TIME SERIES FORECASTS
16 THE BAGIDIS DISTANCE: ABOUT A FRACTAL TOPOLOGY, WITH APPLICATIONS TO
FUNCTIONAL CLASSIFICATION AND PREDICTION
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
MODELING AND STOCHASTIC LEARNING FOR FORECASTING IN HIGH DIMENSIONS
/
: 2015
ABSTRACT / INHALTSTEXT
THE CHAPTERS IN THIS VOLUME STRESS THE NEED FOR ADVANCES IN THEORETICAL
UNDERSTANDING TO GO HAND-IN-HAND WITH THE WIDESPREAD PRACTICAL
APPLICATION OF FORECASTING IN INDUSTRY. FORECASTING AND TIME SERIES
PREDICTION HAVE ENJOYED CONSIDERABLE ATTENTION OVER THE LAST FEW
DECADES, FOSTERED BY IMPRESSIVE ADVANCES IN OBSERVATIONAL CAPABILITIES
AND MEASUREMENT PROCEDURES. ON JUNE 5-7, 2013, AN INTERNATIONAL WORKSHOP
ON INDUSTRY PRACTICES FOR FORECASTING WAS HELD IN PARIS, FRANCE,
ORGANIZED AND SUPPORTED BY THE OSIRIS DEPARTMENT OF ELECTRICITE DE
FRANCE RESEARCH AND DEVELOPMENT DIVISION. IN KEEPING WITH TRADITION,
BOTH THEORETICAL STATISTICAL RESULTS AND PRACTICAL CONTRIBUTIONS ON THIS
ACTIVE FIELD OF STATISTICAL RESEARCH AND ON FORECASTING ISSUES IN A
RAPIDLY EVOLVING INDUSTRIAL ENVIRONMENT ARE PRESENTED. THE VOLUME
REFLECTS THE BROAD SPECTRUM OF THE CONFERENCE, INCLUDING 16 ARTICLES
CONTRIBUTED BY SPECIALISTS IN VARIOUS AREAS. THE MATERIAL COMPILED IS
BROAD IN SCOPE AND RANGES FROM NEW FINDINGS ON FORECASTING IN INDUSTRY
AND IN TIME SERIES, ON NONPARAMETRIC AND FUNCTIONAL METHODS, AND ON
ON-LINE MACHINE LEARNING FOR FORECASTING, TO THE LATEST DEVELOPMENTS IN
TOOLS FOR HIGH DIMENSION AND COMPLEX DATA ANALYSIS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
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| institution | BVB |
| isbn | 9783319187327 |
| issn | 0930-0325 |
| language | English |
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| spelling | Modeling and stochastic learning for forecasting in high dimensions Anestis Antoniadis ..., ed. Cham [u.a.] Springer 2015 1 Online-Ressource (X, 339 S.) 105 illus., 49 illus. in color txt rdacontent c rdamedia cr rdacarrier Lecture notes in statistics 217 0930-0325 Statistics Computer science Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Mathematical Modeling and Industrial Mathematics Probability and Statistics in Computer Science Informatik Statistik Antoniadis, Anestis Sonstige oth Erscheint auch als Druckausgabe 978-3-319-18731-0 Lecture Notes in Statistics 217 (DE-604)BV036592911 217 https://doi.org/10.1007/978-3-319-18732-7 Verlag Volltext Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028101546&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028101546&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Abstract |
| spellingShingle | Modeling and stochastic learning for forecasting in high dimensions Lecture Notes in Statistics Statistics Computer science Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Mathematical Modeling and Industrial Mathematics Probability and Statistics in Computer Science Informatik Statistik |
| title | Modeling and stochastic learning for forecasting in high dimensions |
| title_auth | Modeling and stochastic learning for forecasting in high dimensions |
| title_exact_search | Modeling and stochastic learning for forecasting in high dimensions |
| title_full | Modeling and stochastic learning for forecasting in high dimensions Anestis Antoniadis ..., ed. |
| title_fullStr | Modeling and stochastic learning for forecasting in high dimensions Anestis Antoniadis ..., ed. |
| title_full_unstemmed | Modeling and stochastic learning for forecasting in high dimensions Anestis Antoniadis ..., ed. |
| title_short | Modeling and stochastic learning for forecasting in high dimensions |
| title_sort | modeling and stochastic learning for forecasting in high dimensions |
| topic | Statistics Computer science Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Mathematical Modeling and Industrial Mathematics Probability and Statistics in Computer Science Informatik Statistik |
| topic_facet | Statistics Computer science Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Mathematical Modeling and Industrial Mathematics Probability and Statistics in Computer Science Informatik Statistik |
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