Presentation Ninja

Create HTML5 slides with R Markdown and the JavaScript library 'remark.js' (< https://remarkjs.com>).

Component-Wise MOEA/D Implementation

Modular implementation of Multiobjective Evolutionary Algorithms based on Decomposition (MOEA/D) [Zhang and Li (2007), ] for quick assembling and testing of new algorithmic components, as well as easy replication of published MOEA/D proposals. The full framework is documented in a paper published in the Journal of Statistical Software [].

Create Visualisations for BART Models

Investigating and visualising Bayesian Additive Regression Tree (BART) (Chipman, H. A., George, E. I., & McCulloch, R. E. 2010) model fits. We construct conventional plots to analyze a model’s performance and stability as well as create new tree-based plots to analyze variable importance, interaction, and tree structure. We employ Value Suppressing Uncertainty Palettes (VSUP) to construct heatmaps that display variable importance and interactions jointly using colour scale to represent posterior uncertainty. Our visualisations are designed to work with the most popular BART R packages available, namely 'BART' Rodney Sparapani and Charles Spanbauer and Robert McCulloch 2021 , 'dbarts' (Vincent Dorie 2023) < https://CRAN.R-project.org/package=dbarts>, and 'bartMachine' (Adam Kapelner and Justin Bleich 2016) .

Calculates the Bidimensional Regression Between Two 2D Configurations

Calculates the bidimensional regression between two 2D configurations following the approach by Tobler (1965).

Bayesian Statistics for 2D/3D Transformations

Fits 2D and 3D geometric transformations via 'Stan' probabilistic programming engine ( Stan Development Team (2021) < https://mc-stan.org>). Returns posterior distribution for individual parameters of the fitted distribution. Allows for computation of LOO and WAIC information criteria (Vehtari A, Gelman A, Gabry J (2017) ) as well as Bayesian R-squared (Gelman A, Goodrich B, Gabry J, and Vehtari A (2018) ).

Improved Text Rendering Support for 'Grid' Graphics

Provides support for rendering of formatted text using 'grid' graphics. Text can be formatted via a minimal subset of 'Markdown', 'HTML', and inline 'CSS' directives, and it can be rendered both with and without word wrap.

Call Rust Code from R using the 'extendr' Crate

Provides functions to compile and load Rust code from R, similar to how 'Rcpp' or 'cpp11' allow easy interfacing with C++ code. Also provides helper functions to create R packages that use Rust code. Under the hood, the Rust crate 'extendr' is used to do all the heavy lifting.

HMMs with Ordered Hidden States and Emission Densities

Inference using a class of Hidden Markov models (HMMs) called 'oHMMed'(ordered HMM with emission densities ): The 'oHMMed' algorithms identify the number of comparably homogeneous regions within observed sequences with autocorrelation patterns. These are modelled as discrete hidden states; the observed data points are then realisations of continuous probability distributions with state-specific means that enable ordering of these distributions. The observed sequence is labelled according to the hidden states, permitting only neighbouring states that are also neighbours within the ordering of their associated distributions. The parameters that characterise these state-specific distributions are then inferred. Relevant for application to genomic sequences, time series, or any other sequence data with serial autocorrelation.

A Common Representation of Time Indices of Different Types

Provides an easy-to-use tind class representing time indices of different types (years, quarters, months, ISO 8601 weeks, dates, time of day, date-time, and arbitrary integer/numeric indices). Includes an extensive collection of functions for calendrical computations (including business applications), index conversions, index parsing, and other operations. Auxiliary classes representing time differences and time intervals (with set operations and index matching functionality) are also provided. All routines have been optimised for speed in order to facilitate computations on large datasets. More details regarding calendars in general and calendrical algorithms can be found in "Calendar FAQ" by Claus Tøndering < https://www.tondering.dk/claus/calendar.html>.

A Sky Illuminance Location Tracker

Calculate geolocations by light using template matching. The routine uses a calibration free optimization of a sky illuminance model to determine locations robustly using a template matching approach, as described by Ekstrom (2004) < https://nipr.repo.nii.ac.jp/records/2496>, and behaviourly informed constraints (step-selection).