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Predictive (Classification and Regression) Models Homologator
Methods to unify the different ways of creating predictive models and their different predictive formats for classification and regression. It includes methods such as K-Nearest Neighbors Schliep, K. P. (2004)
High-Throughput Screening for Plate Based Essays
Can be used to carry out extraction, normalization, quality control (QC), candidate hits identification and visualization for plate based assays, in drug discovery. The package methods were applied in H. W. Choi et al. "Identification of Novel Mast Cell Activators Using Cell-Based High-Throughput Screening", SLAS Discovery 24(6), 2019. This project was funded by the Division of Allergy, Immunology, and Transplantation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contract No. HHSN272201400054C entitled "Adjuvant Discovery For Vaccines Against West Nile Virus and Influenza", awarded to Duke University and lead by Drs. Herman Staats and Soman Abraham.
Fast 'Rcpp' Implementation of Gauss-Hermite Quadrature
Fast, numerically-stable Gauss-Hermite quadrature rules and
utility functions for adaptive GH quadrature. See Liu, Q. and Pierce, D. A.
(1994)
Models for Data from Unmarked Animals
Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023)
Colour Palettes for Data
Colour palettes for data, based on some well known public data sets. Includes helper functions to map absolute values to known palettes, and capture the work of image colour mapping as raster data sets.
Tools for 'Box Geometry Model' (BGM) Files and Topology for the Atlantis Ecosystem Model
Facilities for working with Atlantis box-geometry model (BGM) files. Atlantis is a deterministic, biogeochemical, whole-of-ecosystem model. Functions are provided to read from BGM files directly, preserving their internal topology, as well as helper functions to generate spatial data from these mesh forms. This functionality aims to simplify the creation and modification of box and geometry as well as the ability to integrate with other data sources.
Gravitational and Magnetic Attraction of 3-D Vertical Rectangular Prisms
Computes the gravitational and magnetic anomalies generated by
3-D vertical rectangular prisms at specific observation points using the
method of Plouff (1976)
Tidy Tools for 'Raster' Data
Facilities to work with vector and raster data in efficient repeatable and systematic work flow. Missing functionality in existing packages is included here to allow extraction from raster data with 'simple features' and 'Spatial' types and to make extraction consistent and straightforward. Extract cell numbers from raster data and return the cells as a data frame rather than as lists of matrices or vectors. The functions here allow spatial data to be used without special handling for the format currently in use.
Example BGM Files for the Atlantis Ecosystem Model
A collection of box-geometry model (BGM) files for the Atlantis ecosystem model. Atlantis is a deterministic, biogeochemical, whole-of-ecosystem model (see < http://atlantis.cmar.csiro.au/> for more information).
Raster Georeferencing, Grid Affine Transforms, Cell Abstraction
Tools for raster georeferencing, grid affine transforms, and general raster logic. These functions provide converters between raster specifications, world vector, geotransform, 'RasterIO' window, and 'RasterIO window' in 'sf' package list format. There are functions to offset a matrix by padding any of four corners (useful for vectorizing neighbourhood operations), and helper functions to harvesting user clicks on a graphics device to use for simple georeferencing of images. Methods used are available from < https://en.wikipedia.org/wiki/World_file> and < https://gdal.org/user/raster_data_model.html>.