Holdings: Modern methodology and applications in spatial-temporal modeling

Modern methodology and applications in spatial-temporal modeling:

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Bibliographic Details
Other Authors:	Peters, Gareth (Editor), Matsui, Tomoko (Editor)
Format:	Electronic eBook
Language:	English
Published:	Tokyo Springer [2015]
Series:	SpringerBriefs in statistics
Subjects:	Statistics Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistik
Online Access:	DE-634 DE-861 DE-91 DE-19 DE-703 DE-20 DE-739 Volltext Abstract Inhaltsverzeichnis
Physical Description:	1 Online Ressource (XV, 111 Seiten, 17 illus., 4 illus. in color)
ISBN:	9784431553397
ISSN:	2191-544X
DOI:	10.1007/978-4-431-55339-7

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MARC


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Record in the Search Index

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adam_text	MODERN METHODOLOGY AND APPLICATIONS IN SPATIAL-TEMPORAL MODELING / : 2015 ABSTRACT / INHALTSTEXT THIS BOOK PROVIDES A MODERN INTRODUCTORY TUTORIAL ON SPECIALIZED METHODOLOGICAL AND APPLIED ASPECTS OF SPATIAL AND TEMPORAL MODELING. THE AREAS COVERED INVOLVE A RANGE OF TOPICS WHICH REFLECT THE DIVERSITY OF THIS DOMAIN OF RESEARCH ACROSS A NUMBER OF QUANTITATIVE DISCIPLINES. FOR INSTANCE, THE FIRST CHAPTER DEALS WITH NON-PARAMETRIC BAYESIAN INFERENCE VIA A RECENTLY DEVELOPED FRAMEWORK KNOWN AS KERNEL MEAN EMBEDDING WHICH HAS HAD A SIGNIFICANT INFLUENCE IN MACHINE LEARNING DISCIPLINES. THE SECOND CHAPTER TAKES UP NON-PARAMETRIC STATISTICAL METHODS FOR SPATIAL FIELD RECONSTRUCTION AND EXCEEDANCE PROBABILITY ESTIMATION BASED ON GAUSSIAN PROCESS-BASED MODELS IN THE CONTEXT OF WIRELESS SENSOR NETWORK DATA. THE THIRD CHAPTER PRESENTS SIGNAL-PROCESSING METHODS APPLIED TO ACOUSTIC MOOD ANALYSIS BASED ON MUSIC SIGNAL ANALYSIS. THE FOURTH CHAPTER COVERS MODELS THAT ARE APPLICABLE TO TIME SERIES MODELING IN THE DOMAIN OF SPEECH AND LANGUAGE PROCESSING. THIS INCLUDES ASPECTS OF FACTOR ANALYSIS, INDEPENDENT COMPONENT ANALYSIS IN AN UNSUPERVISED LEARNING SETTING. THE CHAPTER MOVES ON TO INCLUDE MORE ADVANCED TOPICS ON GENERALIZED LATENT VARIABLE TOPIC MODELS BASED ON HIERARCHICAL DIRICHLET PROCESSES WHICH RECENTLY HAVE BEEN DEVELOPED IN NON-PARAMETRIC BAYESIAN LITERATURE. THE FINAL CHAPTER DISCUSSES ASPECTS OF DEPENDENCE MODELING, PRIMARILY FOCUSING ON THE ROLE OF EXTREME TAIL-DEPENDENCE MODELING, COPULAS, AND THEIR ROLE IN WIRELESS COMMUNICATIONS SYSTEM MODELS DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. MODERN METHODOLOGY AND APPLICATIONS IN SPATIAL-TEMPORAL MODELING / : 2015 TABLE OF CONTENTS / INHALTSVERZEICHNIS 1 NONPARAMETRIC BAYESIAN INFERENCE WITH KERNEL MEAN EMBEDDING (KENJI FUKUMIZU) 2 HOW TO UTILISE SENSOR NETWORK DATA TO EFFICIENTLY PERFORM MODEL CALIBRATION AND SPATIAL FIELD RECONSTRUCTION (GARETH W. PETERS, IDO NEVAT AND TOMOKO MATSUI) 3 SPEECH AND MUSIC EMOTION RECOGNITION USING GAUSSIAN PROCESSES (KONSTANTIN MARKOV AND TOMOKO MATSUI) 4 TOPIC MODELING FOR SPEECH AND LANGUAGE PROCESSING (JEN-TZUNG CHIEN) DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
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dewey-tens	510 - Mathematics
discipline	Mathematik
doi_str_mv	10.1007/978-4-431-55339-7
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spelling	Modern methodology and applications in spatial-temporal modeling Gareth William Peters, Tomoko Matsui, editors Tokyo Springer [2015] © 2015 1 Online Ressource (XV, 111 Seiten, 17 illus., 4 illus. in color) txt rdacontent c rdamedia cr rdacarrier SpringerBriefs in statistics 2191-544X Statistics Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistik Peters, Gareth (DE-588)1084592576 edt Matsui, Tomoko edt Erscheint auch als Druckausgabe 978-4-431-55338-0 https://doi.org/10.1007/978-4-431-55339-7 Verlag Volltext Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028826747&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Abstract Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028826747&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Modern methodology and applications in spatial-temporal modeling Statistics Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistik
title	Modern methodology and applications in spatial-temporal modeling
title_auth	Modern methodology and applications in spatial-temporal modeling
title_exact_search	Modern methodology and applications in spatial-temporal modeling
title_full	Modern methodology and applications in spatial-temporal modeling Gareth William Peters, Tomoko Matsui, editors
title_fullStr	Modern methodology and applications in spatial-temporal modeling Gareth William Peters, Tomoko Matsui, editors
title_full_unstemmed	Modern methodology and applications in spatial-temporal modeling Gareth William Peters, Tomoko Matsui, editors
title_short	Modern methodology and applications in spatial-temporal modeling
title_sort	modern methodology and applications in spatial temporal modeling
topic	Statistics Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistik
topic_facet	Statistics Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistik
url	https://doi.org/10.1007/978-4-431-55339-7 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028826747&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028826747&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
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