Inference in generalized exponential O–U processes
In this paper, we consider an inference problem in generalized exponential Ornstein–Uhlenbeck processes. Salient features of this paper consists in the fact that, first, we generalized the classical exponential Ornstein–Uhlenbeck processes to the case where the drift coefficient is driven by a perio...
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Veröffentlicht in: | Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems 2023-10, Vol.26 (3), p.581-618 |
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container_title | Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems |
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creator | Lyu, Yunhong Nkurunziza, Sévérien |
description | In this paper, we consider an inference problem in generalized exponential Ornstein–Uhlenbeck processes. Salient features of this paper consists in the fact that, first, we generalized the classical exponential Ornstein–Uhlenbeck processes to the case where the drift coefficient is driven by a period function of time. Second, as opposed to the results in recent literature, the dimension of the drift parameter is considered as unknown. Third, we weaken some assumptions, in recent literature, underlying the asymptotic optimality of some estimators of the drift parameter. We propose the unrestricted maximum likelihood estimator, the restricted maximum likelihood estimator and some shrinkage estimators for the drift parameters. We also derive asymptotic distributional risk of the proposed estimators as well as their relative efficiency. Finally, we present the simulation results which corroborate the theoretical findings. |
doi_str_mv | 10.1007/s11203-023-09291-1 |
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Finally, we present the simulation results which corroborate the theoretical findings.</description><subject>Asymptotic properties</subject><subject>Drift</subject><subject>Inference</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Maximum likelihood estimators</subject><subject>Parameters</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Statistical Theory and Methods</subject><issn>1387-0874</issn><issn>1572-9311</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kM9KAzEQxoMoWKsv4GnB8-pMZrPZPUrxT6HgpZ5Dmk7KlpqtSQvqyXfwDX0Soyt48zDMwPd988FPiHOESwTQVwlRApUg87SyxRIPxAiVlmVLiIf5pkaX0OjqWJyktAaAWqEciWoaPEcOjosuFCsOHO2me-NlwS_bPnDYdXZTPHy-fzwW29g7TonTqTjydpP47HePxfz2Zj65L2cPd9PJ9ax0BLQrF1gjVOyJNDceWVpo2lopVE57aYmsy1JjF6RAS5VlJ71faq0cIFU0FhfD21z8vOe0M-t-H0NuNLJRBEpi3WaXHFwu9ilF9mYbuycbXw2C-YZjBjgmwzE_cAzmEA2hlM1hxfHv9T-pL9U6ZkQ</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Lyu, Yunhong</creator><creator>Nkurunziza, Sévérien</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20231001</creationdate><title>Inference in generalized exponential O–U processes</title><author>Lyu, Yunhong ; Nkurunziza, Sévérien</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c303t-b16104ef337e8f1e2a08965515c7f2a33ac3378ab3507252a0c2ffd775c01343</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Asymptotic properties</topic><topic>Drift</topic><topic>Inference</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Maximum likelihood estimators</topic><topic>Parameters</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Statistical Theory and Methods</topic><toplevel>online_resources</toplevel><creatorcontrib>Lyu, Yunhong</creatorcontrib><creatorcontrib>Nkurunziza, Sévérien</creatorcontrib><collection>CrossRef</collection><jtitle>Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lyu, Yunhong</au><au>Nkurunziza, Sévérien</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Inference in generalized exponential O–U processes</atitle><jtitle>Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems</jtitle><stitle>Stat Inference Stoch Process</stitle><date>2023-10-01</date><risdate>2023</risdate><volume>26</volume><issue>3</issue><spage>581</spage><epage>618</epage><pages>581-618</pages><issn>1387-0874</issn><eissn>1572-9311</eissn><abstract>In this paper, we consider an inference problem in generalized exponential Ornstein–Uhlenbeck processes. 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subjects | Asymptotic properties Drift Inference Mathematics Mathematics and Statistics Maximum likelihood estimators Parameters Probability Theory and Stochastic Processes Statistical Theory and Methods |
title | Inference in generalized exponential O–U processes |
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