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Lifetime Data Analysis

Erschienen in:

02.10.2022

A uniformisation-driven algorithm for inference-related estimation of a phase-type ageing model

verfasst von: Boquan Cheng, Rogemar Mamon

Erschienen in: Lifetime Data Analysis | Ausgabe 1/2023

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Abstract

We develop an efficient algorithm to compute the likelihood of the phase-type ageing model. The proposed algorithm uses the uniformisation method to stabilise the numerical calculation. It also utilises a vectorised formula to only calculate the necessary elements of the probability distribution. Our algorithm, with an error’s upper bound, could be adjusted easily to tackle the likelihood calculation of the Coxian models. Furthermore, we compare the speed and the accuracy of the proposed algorithm with those of the traditional method using the matrix exponential. Our algorithm is faster and more accurate than the traditional method in calculating the likelihood. Based on our experiments, we recommend using 20 sets of randomly-generated initial values for the optimisation to get a reliable estimate for which the evaluated likelihood is close to the maximum likelihood.

Vorheriger Artikel Double bias correction for high-dimensional sparse additive hazards regression with covariate measurement errors

Nächster Artikel A flexible parametric approach for analyzing arbitrarily censored data that are potentially subject to left truncation under the proportional hazards model

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Titel: A uniformisation-driven algorithm for inference-related estimation of a phase-type ageing model
verfasst von: Boquan Cheng
Rogemar Mamon
Publikationsdatum: 02.10.2022
Verlag: Springer US
Erschienen in: Lifetime Data Analysis / Ausgabe 1/2023
Print ISSN: 1380-7870
Elektronische ISSN: 1572-9249
DOI: https://doi.org/10.1007/s10985-022-09577-1

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