For multivariate failure time with auxiliary covariate information,an estimated pseudo-partial-likelihood estimator under the marginal hazard model with distinguishable baseline hazard has been proposed.However,the as...For multivariate failure time with auxiliary covariate information,an estimated pseudo-partial-likelihood estimator under the marginal hazard model with distinguishable baseline hazard has been proposed.However,the asymptotic properties of the corresponding estimated cumulative hazard function have not been studied.In this paper,based on counting process martingale,we use the continuous mapping theorem and Lenglart inequality and prove the consistency of the estimated cumulative hazard function in estimated pseudo-partial-likelihood approach.展开更多
In this paper, based on random left truncated and right censored data, the authors derive strong representations of the cumulative hazard function estimator and the product-limit estimator of the survival function. wh...In this paper, based on random left truncated and right censored data, the authors derive strong representations of the cumulative hazard function estimator and the product-limit estimator of the survival function. which are valid up to a given order statistic of the observations. A precise bound for the errors is obtained which only depends on the index of the last order statistic to be included.展开更多
Single-value prediction such as the End of Life and Remaining Useful Life is a common method of estimating the lifetime of Li-ion batteries.Information from such prediction is limited when the entire degradation patte...Single-value prediction such as the End of Life and Remaining Useful Life is a common method of estimating the lifetime of Li-ion batteries.Information from such prediction is limited when the entire degradation pattern is needed for practical applications such as dynamic adjustment of battery warranty,improved maintenance scheduling,and battery stock management.In this research,a predictive,semi-parametric survival model called the Cox Proportional Hazards is proposed for the prediction of cell degradation in the form of survival probability(battery reliability)and cumulative hazard(battery risk)functions.Once this model is trained,the two functions can be obtained directly for a new cell without having to predict several cogent points.The model is trained on the first 50 cycles of only the voltage profile from either the charge or discharge data regime,implying that our methodology is data region agnostic.The signature method with both desirable mathematical and machine learning properties was adopted as a feature extraction technique.展开更多
A new distribution for the fluctuation of materials＇ lifetime cumulative hazard rate is firstly proposed. The new distribution is extended from the Weibull distribution by adding a sine function. After that, the prop...A new distribution for the fluctuation of materials＇ lifetime cumulative hazard rate is firstly proposed. The new distribution is extended from the Weibull distribution by adding a sine function. After that, the properties of its hazard rate function, cumulative hazard rate function, probability density function and cumulative distribution function are studied. The analysis result shows this distribution can well model the lifetime with variable and periodic hazard rate. Finally, the new distribution is verified with two real data sets as examples to demonstrate its capability.展开更多
基金Supported by the National Natural Science Foundation of China(10771163)
文摘For multivariate failure time with auxiliary covariate information,an estimated pseudo-partial-likelihood estimator under the marginal hazard model with distinguishable baseline hazard has been proposed.However,the asymptotic properties of the corresponding estimated cumulative hazard function have not been studied.In this paper,based on counting process martingale,we use the continuous mapping theorem and Lenglart inequality and prove the consistency of the estimated cumulative hazard function in estimated pseudo-partial-likelihood approach.
文摘In this paper, based on random left truncated and right censored data, the authors derive strong representations of the cumulative hazard function estimator and the product-limit estimator of the survival function. which are valid up to a given order statistic of the observations. A precise bound for the errors is obtained which only depends on the index of the last order statistic to be included.
基金funded by an industry-academia collaborative grant EPSRC EP/R511687/1 awarded by EPSRC&University of Edinburgh,United Kingdom program Impact Acceleration Account(IAA)R.Ibraheem is a Ph.D.student in EPSRC’s MAC-MIGS Centre for Doctoral Training.MAC-MIGS is supported by the UK’s Engineering and Physical Science Research Council(grant number EP/S023291/1)+2 种基金G.dos Reis acknowledges partial support from the FCT-Fundação para a Ciência e a Tecnologia,PortugalI.P.,under the scope of the projects UIDB/00297/2020(https://doi.org/10.54499/UIDB/00297/2020)and UIDP/00297/2020(https://doi.org/10.54499/UIDP/00297/2020)(Center for Mathematics and Applications,NOVA Math)G.dos Reis acknowledges support from the Faraday Institution,United dom King-(grant number FIRG049).
文摘Single-value prediction such as the End of Life and Remaining Useful Life is a common method of estimating the lifetime of Li-ion batteries.Information from such prediction is limited when the entire degradation pattern is needed for practical applications such as dynamic adjustment of battery warranty,improved maintenance scheduling,and battery stock management.In this research,a predictive,semi-parametric survival model called the Cox Proportional Hazards is proposed for the prediction of cell degradation in the form of survival probability(battery reliability)and cumulative hazard(battery risk)functions.Once this model is trained,the two functions can be obtained directly for a new cell without having to predict several cogent points.The model is trained on the first 50 cycles of only the voltage profile from either the charge or discharge data regime,implying that our methodology is data region agnostic.The signature method with both desirable mathematical and machine learning properties was adopted as a feature extraction technique.
基金supported by the National Natural Science Foundation of China under Grant Nos.11461051and 11361036the Natural Science Foundation of Inner Mongolia under Grant No.2014MS0112
文摘A new distribution for the fluctuation of materials＇ lifetime cumulative hazard rate is firstly proposed. The new distribution is extended from the Weibull distribution by adding a sine function. After that, the properties of its hazard rate function, cumulative hazard rate function, probability density function and cumulative distribution function are studied. The analysis result shows this distribution can well model the lifetime with variable and periodic hazard rate. Finally, the new distribution is verified with two real data sets as examples to demonstrate its capability.
