Data on the most popular baby names by sex and year, and for each state in Australia, as provided by the state and territory governments. The quality and quantity of the data varies with the state.

Obtaining Bayes Expected A Posteriori (EAP) individual score estimates based on linear and non-linear extended Exploratoy Factor Analysis solutions that include a correlated-residual structure.

Connects to Google cloud vision <https://cloud.google.com/vision> to perform label detection and repurpose this feature for image classification.

The Sequence of Physical Processes (SPP) framework is a way of interpreting the transient data derived from oscillatory rheological tests. It is designed to allow both the linear and non-linear deformation regimes to be understood within a single unified framework. This code provides a convenient way to determine the SPP framework metrics for a given sample of oscillatory data. It will produce a text file containing the SPP metrics, which the user can then plot using their software of choice. It can also produce a second text file with additional derived data (components of tangent, normal, and binormal vectors), as well as pre-plotted figures if so desired. It is the R version of the Package SPP by Simon Rogers Group for Soft Matter (Simon A. Rogers, Brian M. Erwin, Dimitris Vlassopoulos, Michel Cloitre (2011) <doi:10.1122/1.3544591>).

Given a certain coverage level, obtains simultaneous confidence bands for the survival and cumulative hazard functions such that the area between is minimized. Produces an approximate solution based on local time arguments.

This package provides functionalities and data structures to retrieve, analyze and visualize aviation data. It includes a client interface to the OpenSky API <https://opensky-network.org>. It allows retrieval of flight information, as well as aircraft state vectors.

Utilizes the Black-Scholes-Merton option pricing model to calculate key option analytics and perform graphical analysis of various option strategies. Provides functions to calculate the option premium and option greeks of European-style options.

Trains per-horizon probabilistic ensembles from a univariate time series. It supports rpart', glmnet', and kNN engines with flexible residual distributions and heteroscedastic scale models, weighting variants by calibration-aware scores. A Gaussian/t copula couples the marginals to simulate joint forecast paths, returning quantiles, means, and step increments across horizons.

Computes A-, MV-, D- and E-optimal or near-optimal block designs for two-colour cDNA microarray experiments using the linear fixed effects and mixed effects models where the interest is in a comparison of all possible elementary treatment contrasts. The algorithms used in this package are based on the treatment exchange and array exchange algorithms of Debusho, Gemechu and Haines (2018) <doi:10.1080/03610918.2018.1429617>. The package also provides an optional method of using the graphical user interface (GUI) R package tcltk to ensure that it is user friendly.

This package implements the efficient algorithm by Ortmann and Brandes (2017) <doi:10.1007/s41109-017-0027-2> to compute the orbit-aware frequency distribution of induced and non-induced quads, i.e. subgraphs of size four. Given an edge matrix, data frame, or a graph object (e.g., igraph'), the orbit-aware counts are computed respective each of the edges and nodes.

Data sets for network analysis related to People Analytics. Contains various data sets from the book Handbook of Graphs and Networks in People Analytics by Keith McNulty (2021).

Client for the Office of National Statistics ('ONS') API <https://api.beta.ons.gov.uk/v1>.

Interface to OpenStreetMap API for fetching and saving data from/to the OpenStreetMap database (<https://wiki.openstreetmap.org/wiki/API_v0.6>).

This package provides functions for quickly creating R and Python scripts, as well as Rmarkdown or Quarto documents with automatically assigned name prefixes. Prefixes are either file counts (e.g. "001") or dates (e.g. "2022-09-26").

Estimates optimal number of biomarkers for two-group classification based on microarray data.

Create R plots visualising ontological terms and the relationships between them with various graphical options - Greene et al. 2017 <doi:10.1093/bioinformatics/btw763>.

This package provides tools for checking that the output of an optimization algorithm is indeed at a local mode of the objective function. This is accomplished graphically by calculating all one-dimensional "projection plots" of the objective function, i.e., varying each input variable one at a time with all other elements of the potential solution being fixed. The numerical values in these plots can be readily extracted for the purpose of automated and systematic unit-testing of optimization routines.

Simplifies the creation of xlsx files by providing a high level interface to writing, styling and editing worksheets.

This package provides a wrapper for the OpenTripPlanner <http://www.opentripplanner.org/> REST API. Queries are submitted to the relevant OpenTripPlanner API resource, the response is parsed and useful R objects are returned.

Accesses high resolution raster maps using the OpenStreetMap protocol. Dozens of road, satellite, and topographic map servers are directly supported. Additionally raster maps may be constructed using custom tile servers. Maps can be plotted using either base graphics, or ggplot2. This package is not affiliated with the OpenStreetMap.org mapping project.

This package provides definitions of core classes and methods used by analytic pipelines that query the OMOP (Observational Medical Outcomes Partnership) common data model.

This package provides tools to assist in safely applying user generated objective and derivative function to optimization programs. These are primarily function minimization methods with at most bounds and masks on the parameters. Provides a way to check the basic computation of objective functions that the user provides, along with proposed gradient and Hessian functions, as well as to wrap such functions to avoid failures when inadmissible parameters are provided. Check bounds and masks. Check scaling or optimality conditions. Perform an axial search to seek lower points on the objective function surface. Includes forward, central and backward gradient approximation codes.

An implementation of the Blinder-Oaxaca decomposition for linear regression models.

Growing collection of helper functions for point pattern analysis. Most functions are designed to work with the spatstat (<http://spatstat.org>) package. The focus of most functions are either null models or summary functions for spatial point patterns. For a detailed description of all null models and summary functions, see Wiegand and Moloney (2014, ISBN:9781420082548).