Data and miscellanea to support the book "Introduction to Data analysis with R for Forensic Scientists." This book was written by James Curran and published by CRC Press in 2010 (ISBN: 978-1-4200-8826-7).

Extracts Exchangeable Image File Format (EXIF) metadata, such as camera make and model, ISO speed and the date-time the picture was taken on, from JPEG images. Incorporates the easyexif (https://github.com/mayanklahiri/easyexif) library.

This package performs a compact genetic algorithm search to reduce errors-in-variables bias in linear regression. The algorithm estimates the regression parameters with lower biases and higher variances but mean-square errors (MSEs) are reduced.

Analyzes joint attribute data (e.g., species abundance) that are combinations of continuous and discrete data with Gibbs sampling. Full model and computation details are described in Clark et al. (2018) <doi:10.1002/ecm.1241>.

This package provides a case conversion between common cases like CamelCase and snake_case. Using the rust crate heck <https://github.com/withoutboats/heck> as the backend for a highly performant case conversion for R'.

Utilities to work with data from the Internal Displacement Monitoring Centre (IDMC) (<https://www.internal-displacement.org/>), with convenient functions for loading events data from the IDMC API and transforming events data to daily displacement estimates.

Estimation of latent class models with individual covariates for capture-recapture data. See Bartolucci, F. and Forcina, A. (2022), Estimating the size of a closed population by modeling latent and observed heterogeneity, Biometrics, 80(2), ujae017.

Counting process structure is fundamental to model time varying covariates. This package restructures dataframes in the counting process format for one or more variables. F. W. Dekker, et al. (2008) <doi:10.1038/ki.2008.328>.

This package provides a simple in-memory, LRU cache that can be wrapped around any function to memoize it. The cache is keyed on a hash of the input data (using digest') or on pointer equivalence.

Several functions can be used to analyze neuroimaging data using multivariate methods based on the msma package. The functions used in the book entitled "Multivariate Analysis for Neuroimaging Data" (2021, ISBN-13: 978-0367255329) are contained.

Gibbs sampler for fitting multivariate Bayesian linear regression with shrinkage priors (MBSP), using the three parameter beta normal family. The method is described in Bai and Ghosh (2018) <doi:10.1016/j.jmva.2018.04.010>.

Allows users to conduct multivariate distance matrix regression using analytic p-values and compute measures of effect size. For details on the method, see McArtor, Lubke, & Bergeman (2017) <doi:10.1007/s11336-016-9527-8>.

This package provides functions to read, process and visualize pairwise sequence alignments in the PAF format used by minimap2 and other whole-genome aligners. minimap2 is described by Li H. (2018) <doi:10.1093/bioinformatics/bty191>.

This package provides basic functionality for labeling iso- & anisotropic percolation clusters on 2D & 3D square lattices with various lattice sizes, occupation probabilities, von Neumann & Moore (1,d)-neighborhoods, and random variables weighting the percolation lattice sites.

Efficient design matrix free procedure for solving a soft maximin problem for large scale array-tensor structured models, see Lund, Mogensen and Hansen (2019) <arXiv:1805.02407>. Currently Lasso and SCAD penalized estimation is implemented.

This package provides a bioinformatics tool for the estimation of the tumor purity from sequencing data. It uses the set of putative clonal somatic single nucleotide variants within copy number neutral segments to call tumor cellularity.

This estimates precise weaning ages for a given skeletal population by analyzing the stable nitrogen isotope ratios of them. Bone collagen turnover rates estimated anew and the approximate Bayesian computation (ABC) were adopted in this package.

The package provides different distances measurements to calculate the difference between genesets. Based on these scores the genesets are clustered and visualized as graph. This is all presented in an interactive Shiny application for easy usage.

Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse approximation to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination.

The HiTC package was developed to explore high-throughput "C" data such as 5C or Hi-C. Dedicated R classes as well as standard methods for quality controls, normalization, visualization, and further analysis are also provided.

This package lets you construct paths to your project's files. Use the here function as a drop-in replacement for file.path, it will always locate the files relative to your project root.

This package provides SNP array data from different types of copy-number regions. These regions were identified manually by the authors of the package and may be used to generate realistic data sets with known truth.

This package provides functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.

Reaver performs a brute force attack against an access point's Wi-Fi Protected Setup (WPS) PIN. Once the PIN is found, the WPA passphrase can be recovered and the AP's wireless settings can be reconfigured.