Various functions and algorithms are provided here for solving optimal matching tasks in the context of preclinical cancer studies. Further, various helper and plotting functions are provided for unsupervised and supervised machine learning as well as longitudinal mixed-effects modeling of tumor growth response patterns.

Estimates the density of a spatially distributed animal population sampled with an array of passive detectors, such as traps. Models incorporating distance-dependent detection are fitted by simulation and inverse prediction as proposed by Efford (2004) <doi:10.1111/j.0030-1299.2004.13043.x>.

This is a collection of tools for more efficiently understanding and sharing the results of (primarily) regression analyses. There are also a number of miscellaneous functions for statistical and programming purposes. Support for models produced by the survey and lme4 packages are points of emphasis.

This package contains a collection of useful functions for basic data computation and manipulation, wrapper functions for generating ggplot2 graphics, including statistical model diagnostic plots, methods for computing statistical models quality measures (such as AIC, BIC, r squared, root mean squared error) and general utilities.

This package provides functions to estimate and visualize linear as well as nonlinear impulse responses based on local projections by Jordà (2005) <doi:10.1257/0002828053828518>. The methods and the package are explained in detail in Adämmer (2019) <doi:10.32614/RJ-2019-052>.

Distributions that are typically used for exposure rating in general insurance, in particular to price reinsurance contracts. The vignette shows code snippets to fit the distribution to empirical data. See, e.g., Bernegger (1997) <doi:10.2143/AST.27.1.563208> freely available on-line.

Allows various models for multivariate response variables where each response is assumed to follow double hierarchical generalized linear models. In double hierarchical generalized linear models, the mean, dispersion parameters for variance of random effects, and residual variance can be further modeled as random-effect models.

This package performs nonparametric estimation in mixture cure models, and significance tests for the cure probability. For details, see López-Cheda et al. (2017a) <doi:10.1016/j.csda.2016.08.002> and López-Cheda et al. (2017b) <doi:10.1007/s11749-016-0515-1>.

An implementation of prediction intervals for random-effects meta-analysis: Higgins et al. (2009) <doi:10.1111/j.1467-985X.2008.00552.x>, Partlett and Riley (2017) <doi:10.1002/sim.7140>, and Nagashima et al. (2019) <doi:10.1177/0962280218773520>, <arXiv:1804.01054>.

Method to estimate the spatial influence scales of landscape variables on a response variable. The method is based on Chandler and Hepinstall-Cymerman (2016) Estimating the spatial scales of landscape effects on abundance, Landscape ecology, 31: 1383-1394, <doi:10.1007/s10980-016-0380-z>.

Simulation of event histories with possibly non-linear baseline hazard rate functions, non-linear (time-varying) covariate effect functions, and dependencies on the past of the history. Random generation of event histories is performed using inversion sampling on the cumulative all-cause hazard rate functions.

Imports non-tabular from Excel files into R. Exposes cell content, position and formatting in a tidy structure for further manipulation. Tokenizes Excel formulas. Supports .xlsx and .xlsm via the embedded RapidXML C++ library <https://rapidxml.sourceforge.net>. Does not support .xlsb or .xls'.

Wrapper for using tapkee command line utility, it allows to run it from inside R and catch the results for further analysis and plotting. Tapkee is a program for fast dimension reduction, see package?tapkee and <http://tapkee.lisitsyn.me/> for installation and other details.

Most universities use specific color combinations to express their unique brand identity. The unicol package provides the colors and color palettes of various universities for easy plotting and printing in R. We collect and provide a diverse range of color palettes for creating scientific visualizations.

Range-v3 is an extension of the Standard Template Library that makes its iterators and algorithms more powerful by making them composable. Unlike other range-like solutions which, seek to do away with iterators, in range-v3 ranges are an abstraction layer on top of iterators.

This package implements Freund and Schapire's Adaboost.M1 algorithm and Breiman's Bagging algorithm using classification trees as individual classifiers. Once these classifiers have been trained, they can be used to predict on new data. Also, cross validation estimation of the error can be done.

This package provides tools to more conveniently perform tasks associated with add-on packages. pacman conveniently wraps library and package related functions and names them in an intuitive and consistent fashion. It seeks to combine functionality from lower level functions which can speed up workflow.

This package provides functions for working with the scrypt key derivation functions. Scrypt is a password-based key derivation function created by Colin Percival. The algorithm was specifically designed to make it costly to perform large-scale custom hardware attacks by requiring large amounts of memory.

This package provides tools to create dynamic, submission-ready manuscripts, which conform to American Psychological Association manuscript guidelines. It provides R Markdown document formats for manuscripts (PDF and Word) and revision letters (PDF). Helper functions facilitate reporting statistical analyses or create publication-ready tables and plots.

cl-rmath is a simple, autogenerated foreign interface for the standalone R API libRmath. There has been no effort to provide a high-level interface for the original library, instead, this library is meant to serve as a building block for such an interface.

The fbcp command provided by this package can be used to copy the primary frame buffer to the secondary frame buffer of a Raspberry Pi. It can for example mirror the primary HDMI output to a secondary LCD display connected to the Raspberry Pi board.

Hoe is a rake/rubygems helper for project Rakefiles. It helps manage, maintain, and release projects and includes a dynamic plug-in system allowing for easy extensibility. Hoe ships with plug-ins for all the usual project tasks including rdoc generation, testing, packaging, deployment, and announcement.

Hoe is a rake/rubygems helper for project Rakefiles. It helps manage, maintain, and release projects and includes a dynamic plug-in system allowing for easy extensibility. Hoe ships with plug-ins for all the usual project tasks including rdoc generation, testing, packaging, deployment, and announcement.

Hoe is a rake/rubygems helper for project Rakefiles. It helps manage, maintain, and release projects and includes a dynamic plug-in system allowing for easy extensibility. Hoe ships with plug-ins for all the usual project tasks including rdoc generation, testing, packaging, deployment, and announcement.