12 Mean residual life: Theory and applications

Guess, Frank M.; Proschan, Frank

doi:10.1016/s0169-7161(88)07014-2

Cited by 145 publications

(71 citation statements)

References 19 publications

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“…Guess and Proschan [11] gave an extensive coverage of applications of the MRL in survival analysis, biomedical sciences, life insurance, social studies, economics, demography, maintenance and product quality control and product technology (Lai and Xie [15]). …”

Section: Incomplete Moments the Sth Incomplete Moment Ofmentioning

confidence: 99%

The Marshall-Olkin Additive Weibull Distribution with Variable Shapes for the Hazard Rate

Afify¹,

Cordeiro²,

Yousof³

et al. 2016

HJMS

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We introduce and study the Marshall-Olkin additive Weibull distribution in order to allow a wide variation in the shape of the hazard rate, including increasing, decreasing, bathtub and unimodal shapes. The new distribution generalizes at least eleven lifetime models extant in the literature. Various of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, moments of the residual and reversed residual life functions and order statistics are derived. The parameters of the new distribution are estimated by the maximum likelihood method. We illustrate empirically the superiority of the new model over other distributions by means of a real life data set.

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Section: Incomplete Moments the Sth Incomplete Moment Ofmentioning

confidence: 99%

The Marshall-Olkin Additive Weibull Distribution with Variable Shapes for the Hazard Rate

Afify¹,

Cordeiro²,

Yousof³

et al. 2016

HJMS

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“…If the condition ET < ∞ is satisfied, then the average residua lifetime function of the variable T is with R(t) > 0 defined as: whereas with condition R(t) = 0 it is assumed, that m(t) = 0. The properties of m(t) function were studied in [5,10,11]. The give equality is true:…”

Section: Basic Definitions and Conceptsmentioning

confidence: 99%

Profit Optimalization in Operation Systems

Knopik

Migawa

Wdzięczny

2016

Polish Maritime Research

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“…The MRL function is also useful in actuarial studies relating to life insurance, health science, and so on. We refer interested readers to Guess and Proschan (1988) for a detailed discussion on the applications of the MRL function.…”

Section: Introductionmentioning

confidence: 99%

Additive mean residual life model with latent variables under right censoring

Song¹,

He²,

Pan³

et al. 2018

STAT SINICA

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We propose a novel additive mean residual life model to examine the effects of observable and latent risk factors on the mean residual life function of interest in the presence of right censoring. We use the factor analysis to characterize the latent risk factors on the basis of multiple observed variables. We develop a borrow-strength estimation procedure that incorporates asymptotically distribution-free generalized least square method and corrected estimating equation approach. We establish the asymptotic properties of the proposed estimators. We develop a goodness-of-fit test for model checking. We conduct simulations to evaluate the finite sample performance of the proposed method. The application to the study on chronic kidney disease for type 2 diabetic patients reveals insights into the prevention of such common diabetic complication.

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12 Mean residual life: Theory and applications

Cited by 145 publications

References 19 publications

The Marshall-Olkin Additive Weibull Distribution with Variable Shapes for the Hazard Rate

The Marshall-Olkin Additive Weibull Distribution with Variable Shapes for the Hazard Rate

Profit Optimalization in Operation Systems

Additive mean residual life model with latent variables under right censoring

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