Software

blockstrap

Sample dataframes by group, in the form of a ‘block bootstrap’. Entire groups are returned allowing for a single ‘observation’ to span multiple rows of the dataframe.

Coauthors: Michael Lydeamore, Cash Looi, Kenyon Ng, Mitchell O’Hara-Wild

Available on CRAN

cardinalR

A collection of functions to generate a large variety of structures in high dimensions. These data structures are useful for testing, validating, and improving algorithms used in dimensionality reduction, clustering, machine learning, and visualization.

Coauthors: Michael Lydeamore, Cash Looi, Kenyon Ng, Mitchell O’Hara-Wild

Available on CRAN

condensr

Helps automate ‘Quarto’ website creation for small academic groups. Builds a database-like structure of people, projects and publications, linking them together with a string-based ID system. Then, provides functions to automate production of clean markdown for these structures, and in-built CSS formatting using CSS flexbox.

Coauthors: Michael Lydeamore, Cash Looi, Kenyon Ng, Mitchell O’Hara-Wild

Available on CRAN

HospitalNetwork

Set of tools to help interested researchers to build hospital networks from data on hospitalized patients transferred between hospitals. Methods provided have been used in Donker T, Wallinga J, Grundmann H. (2010) doi:10.1371/journal.pcbi.1000715, and Nekkab N, Crépey P, Astagneau P, Opatowski L, Temime L. (2020) doi:10.1038/s41598-020-71212-6.

Coauthors: Michael Lydeamore, Cash Looi, Kenyon Ng, Mitchell O’Hara-Wild

Available on CRAN

mapycusmaximus

Focus-glue-context (FGC) fisheye transformations to two-dimensional coordinates and spatial vector geometries. Implements a smooth radial distortion that enlarges a focal region, transitions through a glue ring, and preserves outside context. Methods build on generalized fisheye views and focus+context mapping. For more details see Furnas (1986) doi:10.1145/22339.22342, Furnas (2006) doi:10.1145/1124772.1124921 and Yamamoto et al. (2009) doi:10.1145/1653771.1653788.

Coauthors: Michael Lydeamore, Cash Looi, Kenyon Ng, Mitchell O’Hara-Wild

Available on CRAN

quollr

To construct a model in 2-D space from 2-D nonlinear dimension reduction data and then lift it to the high-dimensional space. Additionally, provides tools to visualise the model overlay the data in 2-D and high-dimensional space. Furthermore, provides summaries and diagnostics to evaluate the nonlinear dimension reduction layout.

Coauthors: Michael Lydeamore, Cash Looi, Kenyon Ng, Mitchell O’Hara-Wild

Available on CRAN