scholarly journals Analysis on censored quantile residual life model via spline smoothing

2012 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanyuan Ma ◽  
Ying Wei
Keyword(s):  
Residual Life ◽  
Spline Smoothing ◽  
Life Model ◽  
Quantile Residual Life

A general quantile residual life model for length‐biased right‐censored data

2019 ◽  
Vol 46 (4) ◽  
pp. 1191-1205
Author(s):  
Fangfang Bai ◽  
Xuerong Chen ◽  
Yan Chen ◽  
Tao Huang
Keyword(s):  
Censored Data ◽  
Residual Life ◽  
Right Censored Data ◽  
Life Model ◽  
Quantile Residual Life

Cause-specific quantile residual life regression

2015 ◽  
Vol 26 (4) ◽  
pp. 1912-1924 ◽  
Author(s):  
Jeong Youn Lim ◽  
Jong-Hyeon Jeong
Keyword(s):  
Residual Life ◽  
Fixed Time ◽  
Estimating Equation ◽  
Simulation Studies ◽  
Finite Sample ◽  
Test Statistic ◽  
Life Distribution ◽  
Finite Sample Properties ◽  
Quantile Residual Life ◽  
Log Linear

We propose a cause-specific quantile residual life regression where the cause-specific quantile residual life, defined as the inverse of the cumulative incidence function of the residual life distribution of a specific type of events of interest conditional on a fixed time point, is log-linear in observable covariates. The proposed test statistic for the effects of prognostic factors does not involve estimation of the improper probability density function of the cause-specific residual life distribution under competing risks. The asymptotic distribution of the test statistic is derived. Simulation studies are performed to assess the finite sample properties of the proposed estimating equation and the test statistic. The proposed method is illustrated with a real dataset from a clinical trial on breast cancer.

scholarly journals Study on Life Model of MOV Based on Multiple Parameters and Surge History

2021 ◽  
Author(s):  
RUAN Xiaofei ◽  
Shaoyun JIN ◽  
WEN Weigang ◽  
CHENG Weidong
Keyword(s):  
Life Prediction ◽  
Residual Life ◽  
Cumulative Effect ◽  
Degradation Process ◽  
Life Assessment ◽  
Lightning Protection ◽  
Multiple Parameters ◽  
History Information ◽  
Life Model ◽  
Metal Oxide Varistor

Abstract With the advance of intelligent operation and maintenance in china railways, the requirement of condition monitoring and remaining life prediction for lightning protection equipment has become increasingly urgent. MOV(Metal Oxide Varistor) is the key component of railway surge protector, and it is necessary to study the description model of its degradation process. The output of the model that uses a single parameter to characterize degradation is more prone to contingency, and cannot truly and fully reflect the life state of the MOV. The degradation of MOV is a cumulative effect, and its life model should consider the surge history information. In view of the above problems, a prediction model of the residual life value of MOV is given by combining various degradation related parameters and surge history. Firstly, nine degradation related parameters are fused to construct degradation core. Then, the degradation core and surge history are fused through Markov chain to build a life model of MOV. Then, the model is calibrated with experimental data. Finally, the model is validated and analyzed by experiments. The model can describe the degradation process of MOV more comprehensively and accurately, and can predict the residual life value at the same time, and it has potential application in the life assessment of surge protective devices.

scholarly journals Comparing quantile residual life functions by confidence bands

2011 ◽  
Vol 18 (2) ◽  
pp. 195-214 ◽  
Author(s):  
Alba M. Franco-Pereira ◽  
Rosa E. Lillo ◽  
Juan Romo
Keyword(s):  
Residual Life ◽  
Confidence Bands ◽  
Quantile Residual Life

Random Effect Additive Mean Residual Life Model

2016 ◽  
Vol 65 (2) ◽  
pp. 860-866 ◽  
Author(s):  
M. Kayid ◽  
S. Izadkhah ◽  
D. ALmufarrej
Keyword(s):  
Residual Life ◽  
Random Effect ◽  
Mean Residual Life ◽  
Life Model
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