Skip to content
DraconiticResearch
Search Sources API
186,541 studies31 sourcesUpdated 17 min ago
PreprintarXiv licencearXiv

The LR1 Lifetime Distribution: Properties, Nonmonotone Hazard, and Statistical Inference

Abstract

The LR1 distribution links an exponential lifetime and a four-stage gamma lifetime through a single positive parameter λ. Their rates, 2λ and λ/2, have a fixed ratio, whereas the exponential mixing probability λ2/(1+λ2) changes with the parameter. This restriction produces a hazard that decreases near zero and eventually increases toward λ/2 for every λ>0. We establish this behavior analytically and obtain an explicit parameter threshold separating decreasing densities from densities with an interior local peak. Distributional calculations provide survival probabilities, moments, transforms, truncated moments, quantiles, order statistics, and reliability summaries. The density at zero establishes identifiability, and strict decrease of the mean ensures a unique moment estimate for every positive sample mean. Likelihood inference includes the score, observed information, a constrained expectation--maximization algorithm, and asymptotic confidence limits; spacing estimation and the likelihood under independent right censoring are also described. Eight Monte Carlo settings, comprising 4,000 generated datasets, quantify the error of likelihood and moment estimators and the coverage of log-scale intervals. The results apply in a fixed working time unit and concern mathematical properties and correctly specified simulation, rather than demonstrated superiority on observed data.

Related

  1. The Wrapped Q-Lindley Distribution: A New Circular Model with Statistical Properties, Classical and Bayesian Inference, and Applications to Directional Data
    Swapnil Swagat Phookan, Sajadul Hussain, Partha Jyoti Hazarika +2
    AxiomsPeer-reviewedCC BY 4.0StatisticsCrossref
  2. Statistical inference and applications of Kumaraswamy Odd Perks power Lomax distribution
    Aleena Thampi, Vasili B. V. Nagarjuna
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textStatisticsCrossref
  3. The Topp-Leone XLindley Distribution: Properties, Estimation and Applications to Lifetime Data
    Saileshwari M, Rajesh Moharana, Kousik Maiti
    arXivPreprintarXiv licenceFull textStatisticsarXiv
  4. The LR2 Lifetime Distribution: Rate Crossing, Reliability Properties, and Estimation
    Lalita Singh
    arXivPreprintarXiv licenceFull textStatisticsarXiv
  5. Second-Order Least Squares Method for Statistical Inference in Linear Models with Asymmetric Errors
    Sanha Kil, Yuliya V. Martsynyuk, Liqun Wang
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
BibTeX
@misc{singh2026lifetime,
  title = {{The LR1 Lifetime Distribution: Properties, Nonmonotone Hazard, and Statistical Inference}},
  author = {Lalita Singh},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.24575},
  eprint = {2610.24575},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.24575},
}
RIS
TY  - UNPB
TI  - The LR1 Lifetime Distribution: Properties, Nonmonotone Hazard, and Statistical Inference
AU  - Lalita Singh
PY  - 2026
DA  - 2026/10/17
PB  - arXiv
DO  - 10.48550/arxiv.2610.24575
UR  - https://arxiv.org/abs/2610.24575
AB  - The LR1 distribution links an exponential lifetime and a four-stage gamma lifetime through a single positive parameter λ. Their rates, 2λ and λ/2, have a fixed ratio, whereas the exponential mixing probability λ^2/(1+λ^2) changes with the parameter. This restriction produces a hazard that decreases near zero and eventually increases toward λ/2 for every λ>0. We establish this behavior analytically and obtain an explicit parameter threshold separating decreasing densities from densities with an interior local peak. Distributional calculations provide survival probabilities, moments, transforms, truncated moments, quantiles, order statistics, and reliability summaries. The density at zero establishes identifiability, and strict decrease of the mean ensures a unique moment estimate for every positive sample mean. Likelihood inference includes the score, observed information, a constrained expectation--maximization algorithm, and asymptotic confidence limits; spacing estimation and the likelihood under independent right censoring are also described. Eight Monte Carlo settings, comprising 4,000 generated datasets, quantify the error of likelihood and moment estimators and the coverage of log-scale intervals. The results apply in a fixed working time unit and concern mathematical properties and correctly specified simulation, rather than demonstrated superiority on observed data.
ER  -