Filter by aquifers
Graphs of ion ratios (units in meq/L)
Identification and classification of hydrochemical patterns based on an unsupervised 'Machine Learning' model of Gaussian mixtures (GMM)
Compositional coordinates biplot (main plot of considered classes)
Articles, books and academic papers
Chris, F., & Adrian, E. R. (2006).Some Applications of Model-Based Clustering in Chemistry. R news.
Egozcue, J. J., Pawlowsky-Glahn, V., & Mateu-Figueras, G. (2003). Isometric Logratio Transformations for Compositional Data Analysis. 35. https://doi.org/10.1023/A:1023818214614
Filzmoser, P., Hron, K., & Reimann, C. (2009). Univariate statistical analysis of environmental (compositional) data: Problems and possibilities. Science of the Total Environment.
Fraley, C., & Raftery, A. E. (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association;.
Fraley, C., & Raftery, A. E. (2007). Model-based Methods of Classification: Using the mclust Software in Chemometrics. Journal of Statistical Software.
Fraley, C., Raftery, A. E., Murphy, T. B., & Scrucca, L. (2012). mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Washington.
JA, P.-A. J.-F. (2015). zCompositions – R package for multivariate imputation of left-censored data under a compositional approach. Chemometrics and Intelligence Laboratory Systems, 143: 85-96.
Javier, P. A., & Jodep Antoni, M.-F. (2015). zCompositions -¬ R package for multivariate imputation of left-censored data under a compositional approach. ScienceDirect.
Martin, A. T., & Wing, H. W. (2009). The Calculation of Posterior Distributions by Data Augmentation. Journal of the American Statistical Association.
Orriols, E. (2023). Anàlisi, disseny i implementació d’un quadre de comandament (dashboard) interactiu a la web basat en R-Shiny per l’anàlisi i explotació de la Base de Dades del Mapa Hidrogeològic de Catalunya. Projecte Final de Màster, Màster universitari en Estadística i Investigació Operativa (UPC-UB). https://hdl.handle.net/2117/390724 .
Palarea-Albaladejo J, M.-F. J. (2014). A bootstrap estimation scheme for chemical compositional data with nondetects. Journal of Chemometrics , 585-599.
Piper, A. (1944). A Graphic Procedure in the Geochemical Interpretation of Water-Analyses. Eos. Transactions American Geophysical Union , 25, 914-928. http://dx.doi.org/10.1029/TR025i006p00914
Scrucca, L. (2009). Dimension reduction for model-based clustering. Springer Science+Business Media.
Scrucca, L (2018). Graphical Tools for Model-based Mixture Discriminant Analysis.
Stiff, H. A. (1951). The interpretation of chemical water analysis by means of patterns. Journal of Petroleum Technology , 3(10), 15–17. https://doi.org/10.2118/951376-G
R packages and manuals
Allaire, J., Xie, Y., Dervieux, C., McPherson, J., Luraschi, J., Ushey, K., Atkins, A., Wickham, H., Cheng, J., Chang, W., & Iannone, R. (2023).
rmarkdown: Dynamic Documents for R.; (R package version 2.25)
https://github.com/rstudio/rmarkdown
(accessed October 1, 2021).
Andries, D., & Brown, M. (2023).
geoshaper: Extension of Capabilities of Shiny Leaflet and Leaflet Extras Drawing Tools.; (R package version 0.1.0)
(accessed October 1, 2023).
Appelhans, T. (2023).
leafem: 'leaflet' Extensions for 'mapview'; (R package version 0.2.3).
https://CRAN.R-project.org/package=leafem
(accessed October 1, 2023).
Attali, D. (2021).
shinyjs: Easily Improve the User Experience of Your Shiny Apps in Seconds.; (R package version 2.1.0).
https://CRAN.R-project.org/package=shinyjs
(accessed October 1, 2021).
Attali, D., & Edwards, T. (2021).
shinyalert: Easily Create Pretty Popup Messages (Modals) in 'Shiny'; (R package version 3.0.0).
https://CRAN.R-project.org/package=shinyalert
(accessed October 1, 2021).
Bailey, E. (2022).
shinyBS: Twitter Bootstrap Components for Shiny; (R package version 0.7.1).
https://CRAN.R-project.org/package=shinyBS
(accessed October 1, 2023).
Cheng, J., Karambelkar, B., & Xie, Y. (2021).
leaflet: Create Interactive Web Maps with the JavaScript 'Leaflet' (R package version 2.0.4.1)
https://CRAN.R-project.org/package=leaflet
(accessed October 1, 2021).
Cheng, J., Sievert, C., Schloerke, B., Chang, W., Xie, Y., & Allen, J. (2023).
htmltools: Tools for HTML (R package version 0.5.6.1).
https://CRAN.R-project.org/package=htmltools
(accessed October 1, 2023).
Fraley, C; Raftery, A.E , (2002).
Model-based clustering, discriminant analysis, and density estimation.; 2002;
Journal of the American Statistical Association; Jun 2002; 97, 458; ABI/INFORM Global
pg. 611.
English, M. (2017).
hydrogeo: Groundwater Data Presentation and Interpretation.; (R package version 0.6-1).
https://CRAN.R-project.org/package=hydrogeo
(accessed October 1, 2021).
Gohel, D., & Skintzos, P. (2023).
ggiraph: Make 'ggplot2' Graphics Interactive (R package version 0.8.71).
https://CRAN.R-project.org/package=ggiraph
(accessed October 1, 2023).
Iannone, R. (2021).
fontawesome: Easily Work with 'Font Awesome' Icons (R package version 0.2.2).
https://CRAN.R-project.org/package=fontawesome
(accessed October 1, 2021).
Karambelkar, B., & Schloerke, B. (2018).
leaflet.extras: Extra Functionality for 'leaflet' Package (R package version 1.0.0).
https://CRAN.R-project.org/package=leaflet.extras
(accessed October 1, 2021).
Merlino, A., & Howard, P. (2021).
shinyFeedback: Display User Feedback in Shiny Apps (R package version 0.4.0).
https://CRAN.R-project.org/package=shinyFeedback
(accessed October 1, 2021).
Nowicki, J., Krzemiński, D., Igras, K., & Sobolewski, J. (2023).
shiny.i18n: Shiny Applications Internationalization.
https://CRAN.R-project.org/package=shiny.i18n
(accessed October 1, 2023).
Palarea-Albaladejo, J., & Martín-Fernández, J. A. (2015).
zCompositions: R package for multivariate imputation of left-censored data under a compositional approach.
(accessed October 1, 2021).
Pebesma, E., & Bivand, R. (2005).
Classes and methods for spatial data in R.
https://CRAN.R-project.org/doc/Rnews/
(accessed October 1, 2021).
Perrier, V., Meyer, F., & Granjon, D. (2023).
shinyWidgets: Custom Inputs Widgets for Shiny; (R package version 0.8.0).
https://CRAN.R-project.org/package=shinyWidgets
(accessed October 1, 2021).
Scrucca, L., Fop, M., Murphy, T. B., & Raftery, A. E. (2016).
mclust: clustering, classification and density estimation using Gaussian finite mixture models. The R Journal, 8(1), 289–317.
https://doi.org/10.32614/RJ-2016-021
(accessed October 1, 2021).
Sievert, C. (2020).
Plotly: Interactive Web-Based Data Visualization with R, plotly, and shiny;. Chapman and Hall/CRC.
(accessed October 1, 2021).
Van den Boogaart, K. G., Tolosana-Delgado, R., & Bren, M. (2023).
compositions: Compositional Data Analysis.; (R package version 2.0-6).
Available online: https://CRAN.R-project.org/package=compositions
(accessed October 1, 2021).
Filzmoser, P. Hron, K. Reimann, C. (2009).
Univariate statistical analysis of environmental (compositional) data:
Problems and possibilities.; 2009
Neuwirth,E. (2022).
RColorBrewer: ColorBrewer Palettes. (R package version 1.1-3)
https://CRAN.R-project.org/package=RColorBrewer
(accessed October 1, 2021).
Chang W, Cheng J, Allaire J, Sievert C, Schloerke B, Xie Y, Allen J, McPherson J, Dipert A, Borges B.(2023).
shiny: Web Application Framework for R.; (R package version 1.7.4)
https://shiny.rstudio.com/
(accessed October 1, 2023).
Chang, W. Borges, B.R. (2018).
shinydashboard: Create Dashboards with 'Shiny'.; (R package version 0.7.1)
https://CRAN.R-project.org/package=shinydashboard
(accessed October 1, 2023).
Wickham, H., & Bryan, J. (2019).
readxl: Read Excel Files (R package version 1.3.1).
https://CRAN.R-project.org/package=readxl
(accessed October 1, 2022).
Wickham, H. (2023).
httr: Tools for Working with URLs and HTTP (R package version 1.4.7).
https://CRAN.R-project.org/package=httr
(accessed October 1, 2025).
Wickham, H., Averick, M., Bryan, J., Chang, W., D’Agostino McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Lin Pedersen, T., Miller, E., Milton Bache, S., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., Takahashi, K., Vaughan, D., Wilke, C., Woo, K., & Yutani, H. (2019).
Welcome to the tidyverse Journal of Open Source Software, 4(43), 1686
https://doi.org/10.21105/joss.01686
(accessed October 1, 2022).
Xie, Y., Cheng, J., & Tan, X. (2023).
DT: A Wrapper of the JavaScript Library 'DataTables' (R package version 0.30).
https://CRAN.R-project.org/package=DT
(accessed October 1, 2023).