Vote for your favorite mineral in #MinCup25! - Chrysotile vs. Pectolite
Two new minerals to launch this year's cup! Hazardous (but useful!) chrysotile faces off against stunning gem pectolite.
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Liu, Xiong-Feng, Tang, Xiao-Song, Li, Dian-Qing, Qi, Xiao-Hui (2020) Jackknifing for modeling sampling properties of soil statistics for geotechnical reliability analysis. Computers and Geotechnics, 125. 103685pp. doi:10.1016/j.compgeo.2020.103685

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleJackknifing for modeling sampling properties of soil statistics for geotechnical reliability analysis
JournalComputers and Geotechnics
AuthorsLiu, Xiong-FengAuthor
Tang, Xiao-SongAuthor
Li, Dian-QingAuthor
Qi, Xiao-HuiAuthor
Year2020 (September)Volume125
PublisherElsevier BV
DOIdoi:10.1016/j.compgeo.2020.103685Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID13020121Long-form Identifiermindat:1:5:13020121:0
GUID0
Full ReferenceLiu, Xiong-Feng, Tang, Xiao-Song, Li, Dian-Qing, Qi, Xiao-Hui (2020) Jackknifing for modeling sampling properties of soil statistics for geotechnical reliability analysis. Computers and Geotechnics, 125. 103685pp. doi:10.1016/j.compgeo.2020.103685
Plain TextLiu, Xiong-Feng, Tang, Xiao-Song, Li, Dian-Qing, Qi, Xiao-Hui (2020) Jackknifing for modeling sampling properties of soil statistics for geotechnical reliability analysis. Computers and Geotechnics, 125. 103685pp. doi:10.1016/j.compgeo.2020.103685
In(2020) Computers and Geotechnics Vol. 125. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Tang, Xiao-Song, Wang, Mao-Xin, Li, Dian-Qing (2020) Modeling multivariate cross-correlated geotechnical random fields using vine copulas for slope reliability analysis. Computers and Geotechnics, 127. 103784pp. doi:10.1016/j.compgeo.2020.103784
Wang, Mao-Xin, Tang, Xiao-Song, Li, Dian-Qing, Qi, Xiao-Hui (2020) Subset simulation for efficient slope reliability analysis involving copula-based cross-correlated random fields. Computers and Geotechnics, 118. 103326 doi:10.1016/j.compgeo.2019.103326
LĂĽ, Tian-Jian, Tang, Xiao-Song, Li, Dian-Qing, Qi, Xiao-Hui (2020) Modeling multivariate distribution of multiple soil parameters using vine copula model. Computers and Geotechnics, 118. 103340 doi:10.1016/j.compgeo.2019.103340
Tang, Xiao-Song, Huang, Han-Bing, Liu, Xiong-Feng, Li, Dian-Qing, Liu, Yong (2023) Efficient Bayesian method for characterizing multiple soil parameters using parametric bootstrap. Computers and Geotechnics, 156. 105296 doi:10.1016/j.compgeo.2023.105296
Tang, Xiao-Song, Wang, Mao-Xin, Li, Dian-Qing (2021) Reply to the discussion on “Modeling multivariate cross-correlated geotechnical random fields using vine copulas for slope reliability analysis”. Computers and Geotechnics, 132. 104023pp. doi:10.1016/j.compgeo.2021.104023
Tang, Xiao-Song, Lin, Xin, Li, Dian-Qing, Wang, Shun (2024) Practical copula-based FORM for efficient slope reliability analysis involving correlated non-normal variables. Computers and Geotechnics, 172. 106451 doi:10.1016/j.compgeo.2024.106451
Ke, Qin; Li, Dian-Qing; Tang, Xiao-Song (2025) NGBoost-based probabilistic surrogate modeling for rockfill dam settlements considering rockfill spatial variability. Computers and Geotechnics, 188. doi:10.1016/j.compgeo.2025.107536
Tang, Xiao-Song, Li, Dian-Qing, Chen, Yi-Feng, Zhou, Chuang-Bing, Zhang, Li-Min (2012) Improved knowledge-based clustered partitioning approach and its application to slope reliability analysis. Computers and Geotechnics, 45. 34-43 doi:10.1016/j.compgeo.2012.05.001
Li, Dian-Qing, Shao, Ke-Bo, Cao, Zi-Jun, Tang, Xiao-Song, Phoon, Kok-Kwang (2016) A generalized surrogate response aided-subset simulation approach for efficient geotechnical reliability-based design. Computers and Geotechnics, 74. 88-101 doi:10.1016/j.compgeo.2015.12.010
Tang, Xiao-Song, Li, Dian-Qing, Rong, Guan, Phoon, Kok-Kwang, Zhou, Chuang-Bing (2013) Impact of copula selection on geotechnical reliability under incomplete probability information. Computers and Geotechnics, 49. 264-278 doi:10.1016/j.compgeo.2012.12.002
Li, Dian-Qing, Zhang, Lei, Tang, Xiao-Song, Zhou, Wei, Li, Jin-Hui, Zhou, Chuang-Bing, Phoon, Kok-Kwang (2015) Bivariate distribution of shear strength parameters using copulas and its impact on geotechnical system reliability. Computers and Geotechnics, 68. 184-195 doi:10.1016/j.compgeo.2015.04.002
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 1, 2025 06:20:34
Go to top of page