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Kobayashi M, Shimizu Y. Threshold estimation for jump-diffusions under small noise asymptotics. STATISTICAL INFERENCE FOR STOCHASTIC PROCESSES 2023. [DOI: 10.1007/s11203-023-09286-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
AbstractWe consider parameter estimation of stochastic differential equations driven by a Wiener process and a compound Poisson process as small noises. The goal is to give a threshold-type quasi-likelihood estimator and show its consistency and asymptotic normality under new asymptotics. One of the novelties of the paper is that we give a new localization argument, which enables us to avoid truncation in the contrast function that has been used in earlier works and to deal with a wider class of jumps in threshold estimation than ever before.
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Kobayashi M, Shimizu Y. Least-squares estimators based on the Adams method for stochastic differential equations with small Lévy noise. JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE 2022. [DOI: 10.1007/s42081-022-00155-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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