Learn how interval varextropy helps measure uncertainty in specific data ranges.
Raheleh Zamini, Somayeh Ghafouri, Faranak Goodarzi
― 5 min read
Mathematics - Statistics Theory
RSSLatest Articles
Quantum PhysicsEstimating Parameters in Quantum Markov Chains
Federico Girotti, Alfred Godley, Mădălin Guţă
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ProbabilityUnderstanding Random Geometric Graphs in Network Theory
Kiril Bangachev, Guy Bresler
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Machine LearningAn Overview of Kernel Ridge Regression Techniques
Parthe Pandit, Zhichao Wang, Yizhe Zhu
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Machine LearningAnalyzing Metaconsistency in Metastable Systems
Zachary P Adams, Sayan Mukherjee
― 6 min read
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A new method for confidently identifying optimal choices from noisy data.
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New methods enhance statistical analysis of non-stationary time series data.
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Exploring how stock price correlation varies throughout the trading day.
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New insights into diffusion models enhance their efficiency and adaptability in data generation.
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An overview of the UCB algorithm and its stability in data collection.
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Introducing a robust test for assessing elliptical models in high-dimensional datasets.
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New methods improve tensor completion accuracy with fewer samples.
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A new method improves model accuracy in statistical analysis.
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A look at improved techniques for identifying changes in various systems.
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A look at combining probabilities and their applications in various fields.
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A clear look at bivariate copulas and their role in modeling relationships between random variables.
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Learn effective methods for testing auto-calibration in regression models for finance and insurance.
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A deep dive into the properties and applications of LSL copulas.
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This article discusses a model for detecting sudden changes in trading activity.
Kim Christensen, Alexei Kolokolov
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New method streamlines analysis of complex data in generalized linear models.
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Exploring how noise affects regression models and their predictions.
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A look at generalized Frechet means and their role in modern data analysis.
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A look into how we find cause-and-effect relationships in data.
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Learn how Gaussian processes address prediction uncertainty in machine learning.
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Exploring the significance of Brownian motion in various fields.
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A new method reveals insights into prediction errors and model complexity.
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Explore the role of eigenvalues in improving statistical analyses and model evaluations.
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Examining the impact of learning rates on predictive performance.
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This study examines the effectiveness of Lasso in high-dimensional diffusion models.
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New method enhances accuracy in analyzing time series data.
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A look at the complexities of normal mixture models in statistics.
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A fresh approach to causal inference using flexible data collection methods.
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Explore stationary-increment harmonizable stable processes and their applications in various fields.
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Exploring new methods in event clustering analysis across various fields.
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A look at recent methods to recover low-rank matrices with fewer observations.
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This article discusses methods to handle bias in distance correlation.
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A deep dive into Wasserstein projections and their applications in statistics.
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A look at the significance and applications of Dickman type processes.
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Learn how kurtosis affects data behavior across various fields.
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New tools improve understanding of Functional Random Forest predictions in healthcare.
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Examining how noise influences behavior and transitions in non-equilibrium systems.
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This article examines new methods for assessing Gaussian random vectors' concentration around average values.
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Learn how likelihood ratios and p-values differ in hypothesis testing.
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A look into improved methods for analyzing functional data.
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