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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.
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)
Time-Frequency Analysis of 1-D Signals
A set of R functions which provide an environment for the Time-Frequency analysis of 1-D signals (and especially for the wavelet and Gabor transforms of noisy signals). It was originally written for Splus by Rene Carmona, Bruno Torresani, and Wen L. Hwang, first at the University of California at Irvine and then at Princeton University. Credit should also be given to Andrea Wang whose functions on the dyadic wavelet transform are included. Rwave is based on the book: "Practical Time-Frequency Analysis: Gabor and Wavelet Transforms with an Implementation in S", by Rene Carmona, Wen L. Hwang and Bruno Torresani (1998, eBook ISBN:978008053942), Academic Press.
Functions and Datasets Required for ST370 Class
Provides functions and datasets required for the ST 370 course at North Carolina State University.
Latent Variable Analysis
Fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.
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.
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.
Parsimonious Gaussian Mixture Models
Carries out model-based clustering or classification using parsimonious Gaussian mixture models. McNicholas and Murphy (2008)
Tools for Standardizing Variables for Regression in R
Tools which allow regression variables to be placed on similar scales, offering computational benefits as well as easing interpretation of regression output.
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>.