Show physics, math and engineering students how an ODE solver is made and how effective R classes can be for the construction of the equations that describe natural phenomena. Inspiration for this work comes from the book on "Computer Simulations in Physics" by Harvey Gould, Jan Tobochnik, and Wolfgang Christian. Book link: <http://www.compadre.org/osp/items/detail.cfm?ID=7375>.

Facilitates the design and generation of optimal color (or symbol) codes that can be used to mark and identify individual animals. These codes are made such that the IDs are robust to partial erasure: even if sections of the code are lost, the entire identity of the animal can be reconstructed. Thus, animal subjects are not confused and no ambiguity is introduced.

Machine learning-based tools to predict DNA methylation of locus-specific repetitive elements (RE) by learning surrounding genetic and epigenetic information. These tools provide genomewide and single-base resolution of DNA methylation prediction on RE that are difficult to measure using array-based or sequencing-based platforms, which enables epigenome-wide association study (EWAS) and differentially methylated region (DMR) analysis on RE.

This package provides functions for studying realized genetic relatedness between people. Users will be able to simulate inheritance patterns given pedigree structures, generate SNP marker data given inheritance patterns, and estimate realized relatedness between pairs of individuals using SNP marker data. See Wang (2017) <doi:10.1534/genetics.116.197004>. This work was supported by National Institutes of Health grants R37 GM-046255.

Applies methods used to estimate animal homerange, but instead of geospatial coordinates, we use isotopic coordinates. The estimation methods include: 1) 2-dimensional bivariate normal kernel utilization density estimator, 2) bivariate normal ellipse estimator, and 3) minimum convex polygon estimator, all applied to stable isotope data. Additionally, functions to determine niche area, polygon overlap between groups and levels (confidence contours) and plotting capabilities.

STG is a method for feature selection in neural network. The procedure is based on probabilistic relaxation of the l0 norm of features, or the count of the number of selected features. The framework simultaneously learns either a nonlinear regression or classification function while selecting a small subset of features. Read more: Yamada et al. (2020) <https://proceedings.mlr.press/v119/yamada20a.html>.

Enables binary package installations on Linux distributions. Provides access to RStudio public repositories at <https://packagemanager.posit.co>, and transparent management of system requirements without administrative privileges. Currently supported distributions are CentOS / RHEL 7-9, and several RHEL derivatives ('Rocky Linux', AlmaLinux', Oracle Linux', and Amazon Linux'), openSUSE / SLES 15.4-5, Debian 11-12, and Ubuntu LTS 20-22.

raylib is a high-level library for video game programming. It aims to abstract away platform and graphics details, allowing you to focus on writing your game.

raylib is a high-level library for video game programming. It aims to abstract away platform and graphics details, allowing you to focus on writing your game.

Wrapper around the Canadian Mortgage and Housing Corporation (CMHC) web interface. It enables programmatic and reproducible access to a wide variety of housing data from CMHC.

This package provides functions to manage databases: select, update, insert, and delete records, list tables, backup tables as CSV files, and import CSV files as tables.

This package provides functions for performing (external) multidimensional unfolding. Restrictions (fixed coordinates or model restrictions) are available for both row and column coordinates in all combinations.

Penalised likelihood estimation of a covariance matrix via the ridge-regularised covglasso estimator described in Cibinel et al. (2024) <doi:10.48550/arXiv.2410.02403>.

This package provides function to apply "Group sequential enrichment design incorporating subgroup selection" (GSED) method proposed by Magnusson and Turnbull (2013) <doi:10.1002/sim.5738>.

Search and download Swiss data and metadata from the I14Y interoperability platform of Switzerland using its public APIs <https://www.i14y.admin.ch/api/index.html>.

This package contains 128 palettes from Color Lisa. All palettes are based on masterpieces from the worlds greatest artists. For more information, see <http://colorlisa.com/>.

This package provides functions for performing and visualizing Local Fisher Discriminant Analysis(LFDA), Kernel Fisher Discriminant Analysis(KLFDA), and Semi-supervised Local Fisher Discriminant Analysis(SELF).

This package provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument are binary. Applicable to both binary and continuous outcomes.

This package provides a mixed collection of useful and semi-useful diverse statistical functions, some of which may even be referenced in The R Primer book.

Perform missing value imputation for biological data using the random forest algorithm, the imputation aim to keep the original mean and standard deviation consistent after imputation.

Noninferiority tests for difference in failure rates at a prespecified control rate or prespecified time. For details, see Fay and Follmann, 2016 <DOI:10.1177/1740774516654861>.

Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Currently the only supported pooled objects are DBI connections.

Estimates QAPE using bootstrap procedures. The residual, parametric and double bootstrap is used. The test of normality using Cholesky decomposition is added. Y pop is defined.

Computes the sBIC for various singular model collections including: binomial mixtures, factor analysis models, Gaussian mixtures, latent forests, latent class analyses, and reduced rank regressions.