Detecting mortality deceleration: likelihood inference and model selection in 
the gamma-Gompertz model

Böhnstedt, Marie; Gampe, Jutta

doi:10.1016/j.spl.2019.02.013

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Detecting mortality deceleration: likelihood inference and model selection in the gamma-Gompertz model

Böhnstedt, M., & Gampe, J. (2019). Detecting mortality deceleration: likelihood inference and model selection in the gamma-Gompertz model. Statistics and Probability Letters, 150, 68-73. doi:10.1016/j.spl.2019.02.013.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0006-B032-A Version Permalink: https://hdl.handle.net/21.11116/0000-0006-B033-9

Genre: Journal Article

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Böhnstedt, Marie¹, Author
Gampe, Jutta¹, Author

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1Max Planck Institute for Demographic Research, ou_3148316

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Abstract: We study the asymptotic properties of the maximum likelihood estimator and the likelihood ratio test in the gamma-Gompertz model for local alternatives. We also show that the standard AIC is biased in this model due to the boundary parameter.

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Dates: Date issued: 2019

Publication Status: Issued

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Rev. Type: Peer

Identifiers: Other: 6123
DOI: 10.1016/j.spl.2019.02.013

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Title: Statistics and Probability Letters

Source Genre: Journal

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Pages: - Volume / Issue: 150 Sequence Number: - Start / End Page: 68 - 73 Identifier: -