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On the asymptotic normality of persistent Betti numbers [PDF]
Advances in Applied Probability, 2019 Persistent Betti numbers are a major tool in persistent homology, a subfield of topological data analysis. Many tools in persistent homology rely on the properties of persistent Betti numbers considered as a two-dimensional stochastic process $ (
Johannes T. N. Krebs, W. Polonik
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On the Asymptotic Normality of Adaptive Multilevel Splitting [PDF]
SIAM/ASA J. Uncertain. Quantification, 2018 Adaptive Multilevel Splitting (AMS for short) is a generic Monte Carlo method for Markov processes that simulates rare events and estimates associated probabilities.
F. Cérou +3 more
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Consistency and asymptotic normality of Latent Block Model estimators [PDF]
Electronic Journal of Statistics, 2017 The Latent Block Model (LBM) is a model-based method to cluster simultaneously the $d$ columns and $n$ rows of a data matrix. Parameter estimation in LBM is a difficult and multifaceted problem.
V. Brault +2 more
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Proximal statistic: Asymptotic normality [PDF]
Statistics & Probability Letters, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Asymptotic normality of recursive algorithms via martingale difference arrays [PDF]
Discrete Mathematics & Theoretical Computer Science, 2001 We propose martingale central limit theorems as an tool to prove asymptotic normality of the costs of certain recursive algorithms which are subjected to random input data.
Werner Schachinger
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Asymptotic normality in the maximum entropy models on graphs with an increasing number of parameters [PDF]
Journal of Multivariate Analysis, 2013 T. Yan, Yunpeng Zhao, H. Qin
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Asymptotic Normality in Linear Regression with Approximately Sparse Structure
Mathematics, 2022 In this paper, we study the asymptotic normality in high-dimensional linear regression. We focus on the case where the covariance matrix of the regression variables has a KMS structure, in asymptotic settings where the number of predictors, p, is ...
Saulius Jokubaitis, Remigijus Leipus
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Local asymptotic normality property for fractional Gaussian noise under high-frequency observations [PDF]
Annals of Statistics, 2016 Local Asymptotic Normality (LAN) property for fractional Gaussian noise under high-frequency observations is proved with a non-diagonal rate matrix depending on the parameter to be estimated.
A. Brouste, M. Fukasawa
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Asymptotic inference for a stochastic differential equation with uniformly distributed time delay [PDF]
, 2015 For affine stochastic differential equation with uniformly distributed time delay the local asymptotic properties of the likelihood function are studied.
Benke, János Marcell, Pap, Gyula
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