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Statistical challenges in modern astronomy V

Overview of attention for book
Cover of 'Statistical challenges in modern astronomy V'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Likelihood-Free Inference in Cosmology: Potential for the Estimation of Luminosity Functions
  3. Altmetric Badge
    Chapter 2 Commentary: Likelihood-Free Inference in Cosmology: Potential for the Estimation of Luminosity Functions
  4. Altmetric Badge
    Chapter 3 Robust, Data-Driven Inference in Non-linear Cosmostatistics
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    Chapter 4 Simulation-Aided Inference in Cosmology
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    Chapter 5 Commentary: Simulation-Aided Inference in Cosmology
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    Chapter 6 The Matter Spectral Density from Lensed Cosmic Microwave Background Observations
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    Chapter 7 Commentary: ‘The Matter Spectral Density from Lensed Cosmic Microwave Background Observations’
  9. Altmetric Badge
    Chapter 8 Needlets Estimation in Cosmology and Astrophysics
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    Chapter 9 Parameter Estimation and Model Selection in Extragalactic Astronomy
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    Chapter 10 Commentary: Bayesian Model Selection and Parameter Estimation
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    Chapter 11 Cosmological Bayesian Model Selection: Recent Advances and Open Challenges
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    Chapter 12 Commentary: Cosmological Bayesian Model Selection
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    Chapter 13 Measurement Error Models in Astronomy
  15. Altmetric Badge
    Chapter 14 Commentary: “Measurement Error Models in Astronomy” by Brandon C. Kelly
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    Chapter 15 Asteroseismology: Bayesian Analysis of Solar-Like Oscillators
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    Chapter 16 Semi-parametric Robust Event Detection for Massive Time-Domain Databases
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    Chapter 17 Bayesian Analysis of Reverberation Mapping Data
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    Chapter 18 Bayesian Mixture Models for Poisson Astronomical Images
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    Chapter 19 Systematic Errors in High-Energy Astrophysics
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    Chapter 20 Hierarchical Bayesian Models for Type Ia Supernova Inference
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    Chapter 21 Bayesian Flux Reconstruction in One and Two Bands
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    Chapter 22 Commentary: Bayesian Analysis Across Astronomy
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    Chapter 23 Sparse Astronomical Data Analysis
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    Chapter 24 Exploiting Non-linear Structure in Astronomical Data for Improved Statistical Inference
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    Chapter 25 Commentary: Exploiting Non-linear Structure in Astronomical Data for Improved Statistical Inference
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    Chapter 26 Surprise Detection in Multivariate Astronomical Data
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    Chapter 27 On Statistical Cross-Identification in Astronomy
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    Chapter 28 Commentary: On Statistical Cross-Identification in Astronomy
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    Chapter 29 Data Compression Methods in Astrophysics
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    Chapter 30 Commentary: Data Compression Methods in Astrophysics
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    Chapter 31 Morphological Image Analysis and Sunspot Classification
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    Chapter 32 Commentary: Morphological Image Analysis and Sunspot Classification
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    Chapter 33 Learning About the Sky Through Simulations
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    Chapter 34 Commentary: Learning About the Sky Through Simulations
  36. Altmetric Badge
    Chapter 35 Statistical Analyses of Data Cubes
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    Chapter 36 Astronomical Transient Detection Controlling the False Discovery Rate
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    Chapter 37 Commentary: Astronomical Transient Detection Controlling the False Discovery Rate
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    Chapter 38 Slepian Wavelet Variances for Regularly and Irregularly Sampled Time Series
  40. Altmetric Badge
    Chapter 39 Commentary: Slepian Wavelet Variances for Regularly and Irregularly Samples Time Series
  41. Altmetric Badge
    Chapter 40 Astrostatistics in the International Arena
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    Chapter 41 The R Statistical Computing Environment
  43. Altmetric Badge
    Chapter 42 Panel Discussion: The Future of Astrostatistics
  44. Altmetric Badge
    Chapter 43 Bayesian Estimation of log N — log S
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    Chapter 44 Techniques for Massive-Data Machine Learning in Astronomy
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    Chapter 45 A Bayesian Approach to Gravitational Lens Model Selection
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    Chapter 46 Identification of Outliers Through Clustering and Semi-supervised Learning for All Sky Surveys
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    Chapter 47 Estimation of Moments on the Sphere by Means of Fast Convolution
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    Chapter 48 Variability Detection by Change-Point Analysis
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    Chapter 49 Evolution as a Confounding Parameter in Scaling Relations for Galaxies
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    Chapter 50 Detecting Galaxy Mergers at High Redshift
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    Chapter 51 Multi-component Analysis of a Sample of Bright X-Ray Selected Active Galactic Nuclei
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    Chapter 52 Applying the Background-Source Separation Algorithm to Chandra Deep Field South Data
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    Chapter 53 Non-Gaussian Physics of the Cosmological Genus Statistic
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    Chapter 54 Modeling Undetectable Flares
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    Chapter 55 An F-Statistic Based Multi-detector Veto for Detector Artifacts in Gravitational Wave Data
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    Chapter 56 Constrained Probability Distributions of Correlation Functions
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    Chapter 57 Improving Weak Lensing Reconstructions in 3D Using Sparsity
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    Chapter 58 Bayesian Predictions from the Semi-analytic Models of Galaxy Formation
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    Chapter 59 Statistical Issues in Galaxy Cluster Cosmology
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    Chapter 60 Statistical Analyses to Understand the Relationship Between the Properties of Exoplanets and Their Host Stars
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    Chapter 61 Identifying High-z Gamma-Ray Burst Candidates Using Random Forest Classification
  63. Altmetric Badge
    Chapter 62 Fitting Distributions of Points Using τ 2
  64. Altmetric Badge
    Chapter 63 Theoretical Power Spectrum Estimation from Cosmic Microwave Background Data
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    Chapter 64 Guilt by Association: Finding Cosmic Ray Sources Using Hierarchical Bayesian Clustering
  66. Altmetric Badge
    Chapter 65 Statistical Differences Between Swift Gamma-Ray Burst Classes Based on γ - and X-ray Observations
  67. Altmetric Badge
    Chapter 66 A Quasi-Gaussian Approximation for the Probability Distribution of Correlation Functions
  68. Altmetric Badge
    Chapter 67 New Insights into Galaxy Structure from GALPHAT
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

twitter
16 X users
googleplus
1 Google+ user

Citations

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19 Dimensions

Readers on

mendeley
30 Mendeley
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Title
Statistical challenges in modern astronomy V
Published by
ADS, January 2013
DOI 10.1007/978-1-4614-3520-4
ISBNs
978-1-4614-3519-8, 978-1-4614-3520-4
Authors

Babu, Gutti Jogesh, Feigelson, Eric D

Editors

Feigelson, Eric D., Babu, G. Jogesh

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 29 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 10%
Student > Master 2 7%
Student > Bachelor 1 3%
Student > Doctoral Student 1 3%
Researcher 1 3%
Other 1 3%
Unknown 21 70%
Readers by discipline Count As %
Unspecified 2 7%
Physics and Astronomy 2 7%
Mathematics 2 7%
Environmental Science 1 3%
Earth and Planetary Sciences 1 3%
Other 1 3%
Unknown 21 70%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 April 2022.
All research outputs
#2,724,784
of 22,959,818 outputs
Outputs from ADS
#1,771
of 37,392 outputs
Outputs of similar age
#28,702
of 281,967 outputs
Outputs of similar age from ADS
#44
of 558 outputs
Altmetric has tracked 22,959,818 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 37,392 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 281,967 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 558 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.