This R Studio report output is available in Appendix C. Exploratory data analysis is an important piece of the puzzle for compiling multi-year data in the pursuit of discovering potential mines; after Quality Assurance and Quality Control assessments, of course. The purpose of this report is to compile the vegetation (logepole pine twig) biogeochemical data collected in 2018 and 2022 to assist in understanding the chemical characteristics of the Proof Project area. The R Studio coding is not published.

Author - Python-Diamond Indicator Neural Network (2021)

These coding companions are designed to take you through the creation of neural networks to classify associated diamond contents for 5 different diamond indicator silicate minerals: G10 garnet (G10), eclogitic garnet (EG), chrome diopside (CRD), olivine (OL) and orthopyroxene (OPX). The csv data files are available and the models can be used on other data.

Author - Python-BC ARIS Prospector Contributions (2020)

Taking a look at the monetary expenditures of prospectors to mineral exploration in British Columbia (Canada) between 1998 and 2018 using data captured by the BC Assessment Report Indexing System (ARIS).

Author - R-BioGeochemistry Project (2019)

Missing, below detection and above detection limit imputation and RQ-Principal Component Analysis (PCA) of geochemical and biogeochemical data for use in mineral exploration and environmental studies.

Includes R scripts:

Censor-ImputeMissing: k-nearest neighbour imputation of missing values

Censor-ImputeUDL: parametric replacement of above detection limit values based on ilr-transformation

PCA-workflow-ImputeBDL-clr-RQPCA: imputation of below detection limit (BDL) values, calculation of centred log-ratio (clr) values and RQ-Principal Component Analysis

BC Publications

Yukon Publications

Academia

Conferences

Coding