English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

In this paper, our proposal consists of incorporating frailty into astatistical methodology for modeling time-to-event data, based onnon-proportional hazards regression model. Specifically, we use the generalizedtime-dependent logistic (GTDL) model with a frailty term introduced in thehazard function to control for unobservable heterogeneity among the samplingunits. We also add a regression in the parameter that measures the effect oftime, since it can directly reflect the influence of covariates on the effectof time-to-failure. The practical relevance of the proposed model isillustrated in a real problem based on a data set for downhole safety valves(DHSVs) used in offshore oil and gas production wells. The reliabilityestimation of DHSVs can be used, among others, to predict the blowoutoccurrence, assess the workover demand and aid decision-making actions.

Incorporation of frailties into a non-proportional hazard regression model and its diagnostics for reliability modeling of downhole safety valves