Simple distribution-free statistical assessment of structural integrity material property data

Kim Wallin (Corresponding Author)

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)

Abstract

The assessment of structural integrity data requires a statistical assessment. However, most statistical analysis methods make some assumption regarding the underlying distribution. Here, a new distribution-free statistical assessment method based on a combination of Rank and Bimodal probability estimates is presented and shown to result in consistent estimates of different probability quantiles. The method is applicable for any data set expressed as a function of two parameters. Data for more than two parameters can always be expressed as different subsets varying only two parameters. In principle, this makes the method applicable to the analysis of more complex data sets. The strength in the statistical analysis method presented lies in the objectiveness of the result. There is no need to make any subjective assumptions regarding the underlying distribution, or of the relationship between the parameters considered.
Original languageEnglish
Pages (from-to)2070-2081
Number of pages12
JournalEngineering Fracture Mechanics
Volume78
Issue number9
DOIs
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed

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Structural integrity
Materials properties
Statistical methods

Keywords

  • Rank probability
  • Binomial probability
  • Statistical assessment
  • Objective estimates
  • Lower bound estimates

Cite this

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Simple distribution-free statistical assessment of structural integrity material property data. / Wallin, Kim (Corresponding Author).

In: Engineering Fracture Mechanics, Vol. 78, No. 9, 2011, p. 2070-2081.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Simple distribution-free statistical assessment of structural integrity material property data

AU - Wallin, Kim

PY - 2011

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N2 - The assessment of structural integrity data requires a statistical assessment. However, most statistical analysis methods make some assumption regarding the underlying distribution. Here, a new distribution-free statistical assessment method based on a combination of Rank and Bimodal probability estimates is presented and shown to result in consistent estimates of different probability quantiles. The method is applicable for any data set expressed as a function of two parameters. Data for more than two parameters can always be expressed as different subsets varying only two parameters. In principle, this makes the method applicable to the analysis of more complex data sets. The strength in the statistical analysis method presented lies in the objectiveness of the result. There is no need to make any subjective assumptions regarding the underlying distribution, or of the relationship between the parameters considered.

AB - The assessment of structural integrity data requires a statistical assessment. However, most statistical analysis methods make some assumption regarding the underlying distribution. Here, a new distribution-free statistical assessment method based on a combination of Rank and Bimodal probability estimates is presented and shown to result in consistent estimates of different probability quantiles. The method is applicable for any data set expressed as a function of two parameters. Data for more than two parameters can always be expressed as different subsets varying only two parameters. In principle, this makes the method applicable to the analysis of more complex data sets. The strength in the statistical analysis method presented lies in the objectiveness of the result. There is no need to make any subjective assumptions regarding the underlying distribution, or of the relationship between the parameters considered.

KW - Rank probability

KW - Binomial probability

KW - Statistical assessment

KW - Objective estimates

KW - Lower bound estimates

U2 - 10.1016/j.engfracmech.2011.04.002

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JF - Engineering Fracture Mechanics

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