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Point Processes in a Metric Space and Their Applications
Mathematics, 2022 Point processes are important in extreme value theory due to their equivalent formulations of two popular models in various applications: the block maxima models and the peak-over-threshold model.
Yuwei Zhao
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Mathematics, 2022 Stute presented the so-called conditional U-statistics generalizing the Nadaraya–Watson estimates of the regression function. Stute demonstrated their pointwise consistency and the asymptotic normality.
Salim Bouzebda, Inass Soukarieh
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Signature of Alzheimer’s Disease in Intestinal Microbiome: Results From the AlzBiom Study
Frontiers in Neuroscience, 2022 BackgroundChanges in intestinal microbiome composition have been described in animal models of Alzheimer’s disease (AD) and AD patients. Here we investigated how well taxonomic and functional intestinal microbiome data and their combination with clinical
Christoph Laske +13 more
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Entropy, 2023 The convergence rate for free-distribution functional data analyses is challenging. It requires some advanced pure mathematics functional analysis tools.
Ouahiba Litimein +4 more
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A Note on Nonparametric Estimation of Conditional Hazard Quantile Function [PDF]
Journal of Risk Analysis and Crisis Response (JRACR), 2017 In this paper, we study an kernel estimator of the conditional hazard quantile function (CHQF) of a scalar response variable Y given a random variable (rv) X taking values in a semi-metric space and using the proposed estimator based of the kernel ...
El Hadj Hamel, Nadia Kadiri, Abbes Rabhi
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Probabilistic Wind Speed Forecasting for Wind Turbine Allocation in the Power Grid
Energies, 2023 To face the growing electricity demand, several countries have adopted the solution of clean energy and use renewable energy sources (e.g., wind and solar) to reinforce the stability of the power network, especially during peak demand periods ...
Mohamed Chaouch
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A Novel Curve Clustering Method for Functional Data: Applications to COVID-19 and Financial Data
Analytics, 2023 Functional data analysis has significantly enriched the landscape of existing data analysis methodologies, providing a new framework for comprehending data structures and extracting valuable insights. This paper is dedicated to addressing functional data
Ting Wei, Bo Wang
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Bayesian Nonparametric Mixture Estimation for Time-Indexed Functional Data in R
Journal of Statistical Software, 2016 We present growfunctions for R that offers Bayesian nonparametric estimation models for analysis of dependent, noisy time series data indexed by a collection of domains.
Terrance D. Savitsky
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Risks, 2018 A functional ARMA-GARCH model for predicting the value-at-risk of the EURUSD exchange rate is introduced. The model implements the yield curve differentials between EUR and the US as exogenous factors. Functional principal component analysis allows us to
Holger Fink, Andreas Fuest, Henry Port
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Categorical Functional Data Analysis. The cfda R Package
Mathematics, 2021 Categorical functional data represented by paths of a stochastic jump process with continuous time and a finite set of states are considered. As an extension of the multiple correspondence analysis to an infinite set of variables, optimal encodings of ...
Cristian Preda +2 more
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