An Introduction to Statistics for Geoscientists
additive logratio transformation
box counting
Cantor set
plot circular data
add points to a circular plot
centred logratio transformation
colour plot
count the number of earthquakes per year
ellipse
exponential transformation
calculate the fractal dimension
library(geostats)
create a Gutenberg-Richter plot
Koch snowflake
kriging
Kolmogorov-Smirnov distance matrix
logistic transformation
mean angle
get the mode of a dataset
Principal Component Analysis of 2D data
3-magnet pendulum experiment
generate bivariate random data
calculate
to conversion
Spurious correlation
semivariogram
Sierpinski carpet
calculate the size-frequency distribution of things
calculate the skewness of a dataset
stereonet
ternary diagrams
von Mises distribution
get x,y plot coordinates of ternary data
Linear regression of X,Y-variables with correlated errors
A collection of datasets and simplified functions for an introductory (geo)statistics module at University College London. Provides functionality for compositional, directional and spatial data, including ternary diagrams, Wulff and Schmidt stereonets, and ordinary kriging interpolation. Implements logistic and (additive and centred) logratio transformations. Computes vector averages and concentration parameters for the von-Mises distribution. Includes a collection of natural and synthetic fractals, and a simulator for deterministic chaos using a magnetic pendulum example. The main purpose of these functions is pedagogical. Researchers can find more complete alternatives for these tools in other packages such as 'compositions', 'robCompositions', 'sp', 'gstat' and 'RFOC'. All the functions are written in plain R, with no compiled code and a minimal number of dependencies. Theoretical background and worked examples are available at <https://tinyurl.com/UCLgeostats/>.