The Effect of Gaussian Noise on Maximum Likelihood Fitting of Gompertz and Weibull Mortality Models with Yeast Lifespan Data
Yazarlar (3)
Emine Güven Düzce Üniversitesi, Türkiye
Dr. Öğr. Üyesi Sevinç AKÇAY Kırşehir Ahi Evran Üniversitesi, Türkiye
Hong Qin
University of Tennessee System, Amerika Birleşik Devletleri
University of Tennessee System, Amerika Birleşik Devletleri
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | EXPERIMENTAL AGING RESEARCH (Q4) | ||
| Dergi ISSN | 0361-073X Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 03-2019 |
| Cilt / Sayı / Sayfa | 45 / 2 / 167–179 | DOI | 10.1080/0361073X.2019.1586105 |
| Makale Linki | http://dx.doi.org/10.1080/0361073x.2019.1586105 | ||
| Özet |
| Background/study context: Empirical lifespan data sets are often studied with the best-fitted mathematical model for aging. Here, we studied how experimental noises can influence the determination of the best-fitted aging model. We investigated the influence of Gaussian white noise in lifespan data sets on the fitting outcomes of two-parameter Gompertz and Weibull mortality models, commonly adopted in aging research.Methods: To un-equivocally demonstrate the effect of Gaussian white noises, we simulated lifespans based on Gompertz and Weibull models with added white noises. To gauge the influence of white noise on model fitting, we defined a single index, , for the difference between the maximal log-likelihoods of the Weibull and Gompertz model fittings. We then applied the approach using experimental replicative lifespan data sets for the laboratory BY4741 and BY4742 wildtype reference … |
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BM Sürdürülebilir Kalkınma Amaçları
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| WoS | 6 |
| Google Scholar | 7 |