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Geocoda: Recognizing and Validating Structural Processes in Geochemical Data. A Workflow on Compositional Data Analysis in Lithogeochemistry

https://doi.org/10.2139/ssrn.4530906
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781119976462openalex-snapshot
Compositional Data Analysis
inferredcites →https://doi.org/10.1007/978-0-387-84858-7openalex-snapshot
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
inferredcites →https://doi.org/10.1007/978-3-319-44811-4_7openalex-snapshot
Recognizing and Validating Structural Processes in Geochemical Data: Examples from a Diamondiferous Kimberlite and a Regional Lake Sediment Geochemical Survey
inferredcites →https://doi.org/10.1007/978-3-642-36809-7openalex-snapshot
Analyzing Compositional Data with R
inferredcites →https://doi.org/10.1007/978-81-322-1173-0_11openalex-snapshot
A Multidisciplinary Approach to the Attawapiskat Kimberlite Field, Canada: Accelerating the Discovery-to-Production Pipeline
inferredcites →https://doi.org/10.1007/978-94-009-4109-0openalex-snapshot
The Statistical Analysis of Compositional Data
inferredcites →https://doi.org/10.1007/bf00635485openalex-snapshot
A contribution to the theory of variation diagrams
inferredcites →https://doi.org/10.1007/bf00890676openalex-snapshot
An objective replacement method for censored geochemical data
inferredcites →https://doi.org/10.1007/bf00911549openalex-snapshot
Effects of non-conserved denominators on pearce element ratio diagrams
inferredcites →https://doi.org/10.1007/s00300-016-2047-2openalex-snapshot
Data reporting and visualization in ecology
inferredcites →https://doi.org/10.1007/s00357-009-9027-yopenalex-snapshot
Distributional Equivalence and Subcompositional Coherence in the Analysis of Compositional Data, Contingency Tables and Ratio-Scale Measurements
inferredcites →https://doi.org/10.1007/s11004-008-9212-2openalex-snapshot
Log-Ratio Analysis Is a Limiting Case of Correspondence Analysis
inferredcites →https://doi.org/10.1007/s11004-011-9338-5openalex-snapshot
Measuring Subcompositional Incoherence
inferredcites →https://doi.org/10.1016/0375-6742(86)90012-9openalex-snapshot
Recognition of alteration in volcanic rocks using statistical analysis of lithogeochemical data
inferredcites →https://doi.org/10.1016/j.acags.2019.100017openalex-snapshot
Amalgamations are valid in compositional data analysis, can be used in agglomerative clustering, and their logratios have an inverse transformation
inferredcites →https://doi.org/10.1016/j.apgeochem.2008.04.027openalex-snapshot
Classification of distinct eruptive phases of the diamondiferous Star kimberlite, Saskatchewan, Canada based on statistical treatment of whole rock geochemical analyses
inferredcites →https://doi.org/10.1016/j.chemolab.2021.104248openalex-snapshot
Comparison of zero replacement strategies for compositional data with large numbers of zeros
inferredcites →https://doi.org/10.1016/j.gexplo.2013.07.013openalex-snapshot
A study of the lake sediment geochemistry of the Melville Peninsula using multivariate methods: Applications for predictive geological mapping
inferredcites →https://doi.org/10.1016/j.gr.2017.02.011openalex-snapshot
Using surface regolith geochemistry to map the major crustal blocks of the Australian continent
inferredcites →https://doi.org/10.1023/a:1007568008032openalex-snapshot
Logratios and Natural Laws in Compositional Data Analysis
inferredcites →https://doi.org/10.1023/a:1014826205533openalex-snapshot
Understanding Perturbation on the Simplex: A Simple Method to Better Visualize and Interpret Compositional Data in Ternary Diagrams
inferredcites →https://doi.org/10.1037/met0000464openalex-snapshot
Compositional data analysis tutorial.
inferredcites →https://doi.org/10.1038/s41598-017-16520-0openalex-snapshot
propr: An R-package for Identifying Proportionally Abundant Features Using Compositional Data Analysis
inferredcites →https://doi.org/10.1080/02664763.2022.2108007openalex-snapshot
Three approaches to supervised learning for compositional data with pairwise logratios
inferredcites →https://doi.org/10.1080/10618600.2012.702494openalex-snapshot
Contribution Biplots
inferredcites →https://doi.org/10.1101/2021.06.04.21258353openalex-snapshot
Robustness and bias of European excess death estimates in 2020 under varying model specifications
inferredcites →https://doi.org/10.1111/1467-9876.00275openalex-snapshot
Biplots of Compositional Data
inferredcites →https://doi.org/10.1111/j.1467-985x.2007.00521_5.xopenalex-snapshot
Compositional Data Analysis in the Geosciences: from Theory to Practice
inferredcites →https://doi.org/10.1111/j.2517-6161.1982.tb01195.xopenalex-snapshot
The Statistical Analysis of Compositional Data
inferredcites →https://doi.org/10.1144/1467-7873/07-169openalex-snapshot
Lithogeochemistry of the Collahuasi porphyry Cu–Mo and epithermal Cu–Ag (–Au) cluster, northern Chile: Pearce element ratio vectors to ore
inferredcites →https://doi.org/10.1144/geochem2019-033openalex-snapshot
Molar element ratio analysis of lithogeochemical data: a toolbox for use in mineral exploration and mining
inferredcites →https://doi.org/10.1144/geochem2021-050openalex-snapshot
Tellus regional stream water geochemistry: environmental and mineral exploration applications
inferredcites →https://doi.org/10.1146/annurev-statistics-042720-124436openalex-snapshot
Compositional Data Analysis
inferredcites →https://doi.org/10.1201/9780429455537openalex-snapshot
Compositional Data Analysis in Practice
inferredcites →https://doi.org/10.1214/22-sts880openalex-snapshot
Aitchison’s Compositional Data Analysis 40 Years on: A Reappraisal
inferredcites →https://doi.org/10.1371/journal.pcbi.1004075openalex-snapshot
Proportionality: A Valid Alternative to Correlation for Relative Data
inferredcites →https://doi.org/10.32614/r.manualsopenalex-snapshot
R: A Language and Environment for Statistical Computing
inferredcites →https://doi.org/10.3389/fmicb.2021.727398openalex-snapshot
Compositional Data Analysis of Microbiome and Any-Omics Datasets: A Validation of the Additive Logratio Transformation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1144/geochem2025-077openalex-snapshot
A workflow for the analysis of multivariate exploration geochemical data
inferred← citeshttps://doi.org/10.3390/min16070700openalex-snapshot
Beyond Traditional Methods: Machine Learning for Geochemical Baselines and Anomaly Detection
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