Ebook: Astrostatistics and Data Mining
Author: Roberto Trotta (auth.) Luis Manuel Sarro Laurent Eyer William O'Mullane Joris De Ridder (eds.)
- Genre: Physics // Astronomy
- Tags: Astronomy Astrophysics and Cosmology, Statistics general, Astrophysics and Astroparticles, Statistical Theory and Methods
- Series: Springer Series in Astrostatistics 2
- Year: 2012
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases.
Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.
This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases.
Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.
This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases.
Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.
Content:
Front Matter....Pages i-xi
Front Matter....Pages 1-1
Recent Advances in Cosmological Bayesian Model Comparison....Pages 3-15
Science from Gaia: How to Deal with a Complex Billion-Source Catalogue and Data Archive....Pages 17-29
Extracting Knowledge from Massive Astronomical Data Sets....Pages 31-45
The Art of Data Science....Pages 47-59
Front Matter....Pages 61-61
The Distribution of Galaxies in Spectral Space....Pages 63-69
Utilizing Astroinformatics to Maximize the Science Return of the Next Generation Virgo Cluster Survey....Pages 71-79
Adjustment of Observational Data to Specific Functional Forms Using a Particle Swarm Algorithm and Differential Evolution: Rotational Curves of a Spiral Galaxy as Case Study....Pages 81-88
Probabilistic Description of Stellar Ensembles....Pages 89-96
Solar System Parameters from the Gaia Small Solar System Object Data....Pages 97-105
Data Management at Gaia Data Processing Centers....Pages 107-115
Hipparcos Variable Star Detection and Classification Efficiency....Pages 117-125
Distributed Genetic Algorithm for Feature Selection in Gaia RVS Spectra: Application to ANN Parameterization....Pages 127-131
Efficient Calculation of Covariances for Astrometric Data in the Gaia Catalogue....Pages 133-141
Bayesian Analysis of Cosmic Structures....Pages 143-154
Generalized Stellar Parametrizer with Gaia Photometry Data....Pages 155-162
Classification of Poorly Time Sampled Light Curves of Periodic Variable Stars....Pages 163-171
Handling Imbalanced Data Sets in Multistage Classification....Pages 173-179
A New Approach to the Optimization of the Extraction of Astrometric and Photometric Information from Multi-wavelength Images in Cosmological Fields....Pages 181-189
Statistical Analysis of Caustic Crossings in Multiply Imaged Quasars....Pages 191-199
Stellar Age and Mass Determination....Pages 201-207
Front Matter....Pages 61-61
Data Mining of the MultiDark Simulation....Pages 209-211
Overcoming Sample Selection Bias in Variable Star Classification....Pages 213-221
Data Mining on Ice....Pages 223-231
The Catalogue of X-Ray Bursts Detected by JEM-X Onboard INTEGRAL....Pages 233-237
The Discrete Source Classifier in Gaia-Apsis....Pages 239-246
A Checklist for Planning Research Data Management....Pages 247-251
Efficient Use of Simultaneous Multi-Band Observations for Variable Star Analysis....Pages 253-261
Parametrization of Binary Stars with Gaia Observations....Pages 263-270
This volume provides an overview of the field of Astrostatistics understood as the sub-discipline dedicated to the statistical analysis of astronomical data. It presents examples of the application of the various methodologies now available to current open issues in astronomical research. The technical aspects related to the scientific analysis of the upcoming petabyte-scale databases are emphasized given the importance that scalable Knowledge Discovery techniques will have for the full exploitation of these databases.
Based on the 2011 Astrostatistics and Data Mining in Large Astronomical Databases conference and school, this volume gathers examples of the work by leading authors in the areas of Astrophysics and Statistics, including a significant contribution from the various teams that prepared for the processing and analysis of the Gaia data.
Content:
Front Matter....Pages i-xi
Front Matter....Pages 1-1
Recent Advances in Cosmological Bayesian Model Comparison....Pages 3-15
Science from Gaia: How to Deal with a Complex Billion-Source Catalogue and Data Archive....Pages 17-29
Extracting Knowledge from Massive Astronomical Data Sets....Pages 31-45
The Art of Data Science....Pages 47-59
Front Matter....Pages 61-61
The Distribution of Galaxies in Spectral Space....Pages 63-69
Utilizing Astroinformatics to Maximize the Science Return of the Next Generation Virgo Cluster Survey....Pages 71-79
Adjustment of Observational Data to Specific Functional Forms Using a Particle Swarm Algorithm and Differential Evolution: Rotational Curves of a Spiral Galaxy as Case Study....Pages 81-88
Probabilistic Description of Stellar Ensembles....Pages 89-96
Solar System Parameters from the Gaia Small Solar System Object Data....Pages 97-105
Data Management at Gaia Data Processing Centers....Pages 107-115
Hipparcos Variable Star Detection and Classification Efficiency....Pages 117-125
Distributed Genetic Algorithm for Feature Selection in Gaia RVS Spectra: Application to ANN Parameterization....Pages 127-131
Efficient Calculation of Covariances for Astrometric Data in the Gaia Catalogue....Pages 133-141
Bayesian Analysis of Cosmic Structures....Pages 143-154
Generalized Stellar Parametrizer with Gaia Photometry Data....Pages 155-162
Classification of Poorly Time Sampled Light Curves of Periodic Variable Stars....Pages 163-171
Handling Imbalanced Data Sets in Multistage Classification....Pages 173-179
A New Approach to the Optimization of the Extraction of Astrometric and Photometric Information from Multi-wavelength Images in Cosmological Fields....Pages 181-189
Statistical Analysis of Caustic Crossings in Multiply Imaged Quasars....Pages 191-199
Stellar Age and Mass Determination....Pages 201-207
Front Matter....Pages 61-61
Data Mining of the MultiDark Simulation....Pages 209-211
Overcoming Sample Selection Bias in Variable Star Classification....Pages 213-221
Data Mining on Ice....Pages 223-231
The Catalogue of X-Ray Bursts Detected by JEM-X Onboard INTEGRAL....Pages 233-237
The Discrete Source Classifier in Gaia-Apsis....Pages 239-246
A Checklist for Planning Research Data Management....Pages 247-251
Efficient Use of Simultaneous Multi-Band Observations for Variable Star Analysis....Pages 253-261
Parametrization of Binary Stars with Gaia Observations....Pages 263-270
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