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2017 MATRIX Annals

Overview of attention for book
Cover of '2017 MATRIX Annals'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Metropolis-Hastings-Within-Gibbs Sampler for Nonlinear Hierarchical-Bayesian Inverse Problems
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    Chapter 2 Sequential Bayesian Inference for Dynamical Systems Using the Finite Volume Method
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    Chapter 3 Correlation Integral Likelihood for Stochastic Differential Equations
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    Chapter 4 A Set Optimization Technique for Domain Reconstruction from Single-Measurement Electrical Impedance Tomography Data
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    Chapter 5 Local Volatility Calibration by Optimal Transport
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    Chapter 6 Likelihood Informed Dimension Reduction for Remote Sensing of Atmospheric Constituent Profiles
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    Chapter 7 Wider Contours and Adaptive Contours
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    Chapter 8 Bayesian Point Set Registration
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    Chapter 9 Optimization Methods for Inverse Problems
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    Chapter 10 Diagonal Form Factors from Non-diagonal Ones
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    Chapter 11 Narayana Number, Chebyshev Polynomial and Motzkin Path on RNA Abstract Shapes
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    Chapter 12 A Curious Mapping Between Supersymmetric Quantum Chains
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    Chapter 13 Remarks on A n ( 1 ) $$\boldsymbol {A^{(1)}_n}$$ Face Weights
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    Chapter 14 Boundary Regularity of Mass-Minimizing Integral Currents and a Question of Almgren
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    Chapter 15 Optimal Transport with Discrete Mean Field Interaction
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    Chapter 16 A Sixth Order Curvature Flow of Plane Curves with Boundary Conditions
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    Chapter 17 Quasilinear Parabolic and Elliptic Equations with Singular Potentials
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    Chapter 18 How to Hear the Corners of a Drum
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    Chapter 19 Nonparametric Bayesian Volatility Estimation
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    Chapter 20 The Exact Asymptotics for Hitting Probability of a Remote Orthant by a Multivariate Lévy Process: The Cramér Case
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    Chapter 21 Parisian Excursion Below a Fixed Level from the Last Record Maximum of Lévy Insurance Risk Process
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    Chapter 22 Simple Group Actions on Arc-Transitive Graphs with Prescribed Transitive Local Action
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    Chapter 23 Biquasiprimitive Oriented Graphs of Valency Four
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    Chapter 24 The Contributions of W.T. Tutte to Matroid Theory
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    Chapter 25 Cluster Decorated Geometric Crystals, Generalized Geometric RSK-Correspondences, and Donaldson-Thomas Transformations
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    Chapter 26 Fields of Definition of Finite Hypergeometric Functions
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    Chapter 27 L-Series and Feynman Integrals
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    Chapter 28 Arithmetic Properties of Hypergeometric Mirror Maps and Dwork’s Congruences
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    Chapter 29 Appell–Lauricella Hypergeometric Functions over Finite Fields, and a New Cubic Transformation Formula
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    Chapter 30 Sequences, Modular Forms and Cellular Integrals
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    Chapter 31 Some Supercongruences for Truncated Hypergeometric Series
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    Chapter 32 The Explicit Formula and a Motivic Splitting
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    Chapter 33 Hypergeometric Supercongruences
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    Chapter 34 Alternate Mirror Families and Hypergeometric Motives
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    Chapter 35 Schwarzian Equations and Equivariant Functions
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    Chapter 36 Hypergeometric Functions over Finite Fields
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    Chapter 37 Supercongruences Occurred to Rigid Hypergeometric Type Calabi–Yau Threefolds
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    Chapter 38 p -Adic Hypergeometrics
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    Chapter 39 On p -Adic Unit-Root Formulas
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    Chapter 40 Triangular Modular Curves
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    Chapter 41 Jacobi Sums and Hecke Grössencharacters
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    Chapter 42 Special Values of Hypergeometric Functions and Periods of CM Elliptic Curves
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    Chapter 43 CY-Operators and L-Functions
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    Chapter 44 A Matrix Theoretic Derivation of the Kalman Filter
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    Chapter 45 Approximate Bayesian Computational Methods for the Inference of Unknown Parameters
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    Chapter 46 The Loop-Weight Changing Operator in the Completely Packed Loop Model
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    Chapter 47 A Note on Optimal Double Spending Attacks
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    Chapter 48 Stochastic Maximum Principle on a Continuous-Time Behavioral Portfolio Model
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    Chapter 49 Number of Claims and Ruin Time for a Refracted Risk Process
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    Chapter 50 Numerical Approximations to Distributions of Weighted Kolmogorov-Smirnov Statistics via Integral Equations
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    Chapter 51 Introduction to Extreme Value Theory: Applications to Risk Analysis and Management
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    Chapter 52 Monotone Sharpe Ratios and Related Measures of Investment Performance
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    Chapter 53 On Chernoff’s Test for a Fractional Brownian Motion
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    Chapter 54 How to Sheafify an Elliptic Quantum Group
Attention for Chapter 19: Nonparametric Bayesian Volatility Estimation
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Chapter title
Nonparametric Bayesian Volatility Estimation
Chapter number 19
Book title
2017 MATRIX Annals
Published in
arXiv, January 2019
DOI 10.1007/978-3-030-04161-8_19
Book ISBNs
978-3-03-004160-1, 978-3-03-004161-8
Authors

Shota Gugushvili, Frank van der Meulen, Moritz Schauer, Peter Spreij, Gugushvili, Shota, der Meulen, Frank van, Schauer, Moritz, Spreij, Peter

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 50%
Unknown 1 50%
Readers by discipline Count As %
Mathematics 1 50%
Unknown 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 01 April 2019.
All research outputs
#13,675,702
of 23,201,298 outputs
Outputs from arXiv
#232,917
of 955,194 outputs
Outputs of similar age
#216,621
of 438,663 outputs
Outputs of similar age from arXiv
#6,297
of 24,447 outputs
Altmetric has tracked 23,201,298 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 955,194 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 73% 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 438,663 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24,447 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.