A new representation method for probability distributions of multimodal and irregular data based on uniform mixture model

DOI10.1007/S10479-019-03236-9zbMath1482.62038OpenAlexW2939901248WikidataQ128056067 ScholiaQ128056067MaRDI QIDQ2115795

Jianxiong Gao, Zongwen An, Xuezong Bai

Publication date: 21 March 2022

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-019-03236-9

zbMATH Keywords

reliabilityrandomnessfatigue crackmultimodal and irregular datauniform mixture model

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Exact distribution theory in statistics (62E15) Approximations to statistical distributions (nonasymptotic) (62E17) Reliability and life testing (62N05)

Related Items (1)

A note on the Gao et al. (2019) uniform mixture model in the case of regression

Cites Work

• A framework of irregularity enlightenment for data pre-processing in data mining
• Most unfavorable deductibles and coverage limits for multiple random risks with Archimedean copulas
• The random field Ising model in a shifted bimodal probability distribution
• Discrete approximations of continuous distributions by maximum entropy
• A multimodal beta distribution with application to economic data
• A multimodal skewed extension of normal distribution: its properties and applications
• On estimating uniform distribution via linear Bayes method

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