Statistical Models to Analyze Failure, Wear, Fatigue, and Degradation Data with Explanatory Variables
From MaRDI portal
Publication:3645025
DOI10.1080/03610920902947519zbMath1175.62108OpenAlexW2101246438MaRDI QIDQ3645025
Mikhail S. Nikulin, Vilijandas B. Bagdonavičius
Publication date: 16 November 2009
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610920902947519
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Point estimation (62F10) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)
Related Items (4)
Joint Analysis of Health Histories, Physiological State, and Survival ⋮ Unnamed Item ⋮ Shocks as Burn-In in Heterogeneous Populations ⋮ Degradation-Based Reliability Modeling of Complex Systems in Dynamic Environments
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Covariates and random effects in a Gamma process model with application to degradation and failure
- A flexible semiparametric transformation model for survival data
- Survival in dynamic environments
- Accelerated degradation models for failure based on geometric Brownian motion and gamma processes
- Semiparametric inference for the accelerated life model with time- dependent covariates
- Inference from accelerated degradation and failure data based on Gaussian process models
- Optimal design in nonparametric life testing
- Statistical planning and inference in accelerated life testing using the CHSS model
- Gaussian models for degradation processes. I: Methods for the analysis of biomarker data
- Generalized proportional hazards model based on modified partial likelihood
- Analysis of joint multiple failure mode and linear degradation data with renewals
- Dynamic regression models for survival data.
- On Heteroscedastic Hazards Regression Models: Theory and Application
- Statistical analysis of redundant systems with ‘warm’ stand-by units
- Partial likelihood
- On the collapsibility of lifetime regression models
- On Nonparametric Estimation in Accelerated Experiments with Step-Stresses
- Analysis of survival data with cross-effects of survival functions
- Estimation in degradation models with explanatory variables
This page was built for publication: Statistical Models to Analyze Failure, Wear, Fatigue, and Degradation Data with Explanatory Variables