ScholarGate
Asistent

Usporedite metode

Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.

Modeli degradacije×Weibullova parametarska regresija preživljenja×
PodručjePouzdanostAnaliza preživljavanja
ObiteljRegression modelSurvival analysis
Godina nastanka19981951
TvoracMeeker, Escobar & LuWaloddi Weibull
VrstaStochastic degradation path modelFully parametric survival regression model
Temeljni izvorMeeker, W. Q., Escobar, L. A., & Lu, C. J. (1998). Accelerated degradation tests: modeling and analysis. Technometrics, 40(2), 89–99. DOI ↗Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗
Drugi naziviAccelerated Degradation Testing, Degradation Path Models, Performance Degradation Analysis, Bozunma Modelleriweibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma
Srodne34
SažetakDegradation models estimate product lifetime by tracking measurable performance characteristics—such as crack length, light output, or insulation resistance—over time rather than waiting for outright failure. Introduced in rigorous form by Meeker, Escobar, and Lu (1998), these models fit a stochastic degradation path to repeated measurements and define failure as the first time the characteristic crosses a predetermined threshold, enabling reliable lifetime inference from accelerated test data with very few or no observed failures.Weibull regression is a fully parametric survival model, formalised by Kalbfleisch and Prentice, that assumes survival times follow a Weibull distribution. A shape parameter controls whether the hazard increases, decreases, or remains constant over time, while covariates shift the scale of the distribution to express how predictors affect survival.
ScholarGateSkup podataka
  1. v1
  2. 1 Izvori
  3. PUBLISHED
  1. v1
  2. 1 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

ScholarGateUsporedite metode: Degradation Models · Weibull Regression. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare