Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Semivariogram matrices"'
Publikováno v:
Applied Computing and Geosciences, Vol 8, Iss , Pp 100044- (2020)
Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors. H
Externí odkaz:
https://doaj.org/article/234c407dd7d542b88ff84edaea66b10f
Publikováno v:
Applied Computing and Geosciences 8(2020), 100044
Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors. H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______4577::eae466aaec8c552c5006ff5a83684bc3
https://www.hzdr.de/publications/Publ-31922-1
https://www.hzdr.de/publications/Publ-31922-1
Publikováno v:
Applied Computing and Geosciences, Vol 8, Iss, Pp 100044-(2020)
Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors. H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dce934ba09f18ae801863de0f9afe897
https://doi.org/10.1016/j.acags.2020.100044
https://doi.org/10.1016/j.acags.2020.100044
Autor:
Cheng, Qing1 (AUTHOR) qingcheng@whu.edu.cn, Xie, Ruixiang1 (AUTHOR) 1725303065@cug.edu.cn, Wu, Jingan2 (AUTHOR) wujg5@mail.sysu.edu.cn, Ye, Fan1 (AUTHOR) yefan@cug.edu.cn
Publikováno v:
Remote Sensing. Mar2024, Vol. 16 Issue 6, p1033. 21p.
Autor:
Mueller, Ute, Ferreira, Jacqueline
Publikováno v:
Mathematical Geosciences; May2012, Vol. 44 Issue 4, p427-448, 22p
Autor:
Ducinskas, Kestutis, Dreiziene, Lina
Publikováno v:
Communications in Statistics: Theory & Methods; 2023, Vol. 52 Issue 9, p3165-3173, 9p
Autor:
Dučinskas, Kęstutis1,2, Dreižienė, Lina1,3 l.dreiziene@gmail.com
Publikováno v:
Lithuanian Journal of Statistics / Lietuvos Statistikos Darbai. 2021, Vol. 60, p1-7. 7p.
Autor:
Heriawan, Mohamad Nur1,2 heriawan@mining.itb.ac.id, Koike, Katsuaki3 koike@gpo.kumamoto-u.ac.jp
Publikováno v:
International Journal of Coal Geology. Feb2008, Vol. 73 Issue 3/4, p307-330. 24p.
Autor:
Ute Mueller, Jacqueline Ferreira
Publikováno v:
Mathematical Geosciences. 44:427-448
To speed up multivariate geostatistical simulation it is common to transform the set of attributes into spatially uncorrelated factors that can be simulated independently. Spatial decorrelation methods are usually based on the diagonalisation of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15653c9dfcc4280b96326e1cd919466f
https://doi.org/10.1007/s11004-012-9384-7
https://doi.org/10.1007/s11004-012-9384-7
Autor:
Ver Hoef, Jay M.
Publikováno v:
Methods in Ecology & Evolution; Jun2018, Vol. 9 Issue 6, p1600-1613, 14p