Semiparametric likelihood inference for heterogeneous survival data under double truncation based on a Poisson birth process

Dörre, Achim

doi:10.1007/s42081-021-00128-w

Cited by 7 publications

(5 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Doubly-truncated data, defined as data subject to left-truncation and right-truncation, arise in field failure analyses for mechanical units. 8,9,76 Parametric inference methods discussed in this paper work for doubly-truncated data [76][77][78][79][80][81] by an appropriate correction to the likelihood function. However, sample sizes under doubly-truncation can be small since samples are available only for those who experience failures within the data collection period.…”

Section: Discussionmentioning

confidence: 99%

Left‐truncated and right‐censored field failure data: Review of parametric analysis for reliability

Emura

Michimae

2022

Quality & Reliability Eng

View full text Add to dashboard Cite

In field reliability analyses, a data collection period is given to monitor the failure events from the field. Left‐truncation arises due to early failures occurring before the data collection period, and right‐censoring arises for late failures occurring beyond the monitoring period. Naïve analyses of left‐truncated and right‐censored data lead to biased estimation of the population lifetime of interest. A variety of models and methods have been developed to analyze the left‐truncated and right‐censored data for field reliability analyses. The goal of the paper is to review the existing models and methods for fitting left‐truncated and right‐censored data. Our review includes the existing statistical models, such as the exponential, Weibull, lognormal, gamma, Gompertz, Lomax, and spline models. We comprehensively review the statistical issues of maximum likelihood estimation, model selection, residual lifetime prediction, and Bayesian methods. Some of these methods are illustrated through the field reliability analysis of the electric power transformer dataset.

show abstract

Section: Discussionmentioning

confidence: 99%

Left‐truncated and right‐censored field failure data: Review of parametric analysis for reliability

Emura

Michimae

2022

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…Indeed, the gamma distribution is the secondary choice to the Weibull, lognormal, and logistic distributions. In applications, the gamma distribution is applied with the lognormal and Weibull distributions [72,74,77] or without any other [78,79].…”

Section: Gamma Distributionmentioning

confidence: 99%

Parametric Distributions for Survival and Reliability Analyses, a Review and Historical Sketch

et al. 2022

View full text Add to dashboard Cite

During its 330 years of history, parametric distributions have been useful for survival and reliability analyses. In this paper, we comprehensively review the historical backgrounds and statistical properties of a number of parametric distributions used in survival and reliability analyses. We provide encyclopedic coverage of the important parametric distributions, which is more extensive than the existing textbooks on survival and reliability analyses. We also explain how these distributions have been adopted in survival and reliability analyses with original and state-of-the-art references. We cover the exponential, Weibull, Rayleigh, lognormal, log-logistic, gamma, generalized gamma, Pareto (types I, II, and IV), Hjorth, Burr (types III and XII), Dagum, exponential power, Gompertz, Birnbaum-Saunders, exponential-logarithmic, piecewise exponential, generalized exponential, exponentiated Weibull, generalized modified Weibull, and spline distributions. We analyze a real dataset for illustration.

show abstract

“…Hong et al [1] separated the samples into two parts: a truncated part (e.g., transformers installed before 1980) and an untruncated part (e.g., transformers installed after 1980), and then combined them into a single likelihood function. This type of truncated field data arises in many other practical applications, where there is a birth process (the installing process) of individuals and a certain data collection period of failure [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Likelihood Inference for Copula Models Based on Left-Truncated and Competing Risks Data from Field Studies

Michimae

Emura

2022

Mathematics

View full text Add to dashboard Cite

Survival and reliability analyses deal with incomplete failure time data, such as censored and truncated data. Recently, the classical left-truncation scheme was generalized to analyze “field data”, defined as samples collected within a fixed period. However, existing competing risks models dealing with left-truncated field data are not flexible enough. We propose copula-based competing risks models for latent failure times, permitting a flexible parametric form. We formulate maximum likelihood estimation methods under the Weibull, lognormal, and gamma distributions for the latent failure times. We conduct simulations to check the performance of the proposed methods. We finally give a real data example. We provide the R code to reproduce the simulations and data analysis results.

show abstract

Semiparametric likelihood inference for heterogeneous survival data under double truncation based on a Poisson birth process

Cited by 7 publications

References 27 publications

Left‐truncated and right‐censored field failure data: Review of parametric analysis for reliability

Left‐truncated and right‐censored field failure data: Review of parametric analysis for reliability

Parametric Distributions for Survival and Reliability Analyses, a Review and Historical Sketch

Likelihood Inference for Copula Models Based on Left-Truncated and Competing Risks Data from Field Studies

Contact Info

Product

Resources

About