This package enables you to read and manipulate genome intervals and signals. It provides functionality similar to command-line tool suites within R, enabling interactive analysis and visualization of genome-scale data.

This package provides functions for summarizing and plotting the output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests of convergence to the equilibrium distribution of the Markov chain.

This package supports twin models that are able to estimate the dynamic behaviour of the variance components in the classical twin models with respect to age using B-splines and P-splines.

This package provides a simple HTTP client, with tools for making HTTP requests, and mocking HTTP requests. The package is built on R6, and takes inspiration from Ruby's faraday gem.

This package provides an easy and simple way to read, write and display bitmap images stored in the TIFF format. It can read and write both files and in-memory raw vectors.

Suit of tools for bi-level meta-analysis. The package can be used in a wide range of applications, including general hypothesis testings, differential expression analysis, functional analysis, and pathway analysis.

Allows the user to implement an address search auto completion menu on shiny text inputs. This is done using the Algolia Places JavaScript library. See <https://community.algolia.com/places/>.

Load Current Population Survey (CPS) microdata into R using the Census Bureau Data API (<https://www.census.gov/data/developers/data-sets.html>), including basic monthly CPS and CPS ASEC microdata.

This package provides a device closing function which is able to crop graphics (e.g., PDF, PNG files) on Unix-like operating systems with the required underlying command-line tools installed.

This package contains functions for estimating generalized parametric mixture and non-mixture cure models <doi:10.1016/j.cmpb.2022.107125>, loss of lifetime, mean residual lifetime, and crude event probabilities.

This package provides functions for fitting a Bayesian model for grouping binary dissimilarity matrices in homogeneous clusters. Currently, it includes methods only for binary data (<doi:10.18637/jss.v100.i16>).

Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.

Convert Leaf Area Index (LAI) from the Normalized Difference Vegetation Index (NDVI) using available equations from literature. Detailed description of conversion equations in Bajocco et al. 2022 <doi:10.3390/rs14153554>.

Use the open source MDB Tools utilities <https://github.com/mdbtools/mdbtools/>. Primarily used for converting proprietary Microsoft Access files to simple text files and then reading those as data frames.

Allow users to obtain basketball statistics for the Australian basketball league NBL'<https://nbl.com.au/>. Stats include play-by-play, shooting locations, results and box scores for teams and players.

An interface to compute poverty and inequality indicators for more than 160 countries and regions from the World Bank's database of household surveys, through the Poverty and Inequality Portal (PIP).

Given a vector of Taylor series coefficients of sufficient length as input, the function returns the numerator and denominator coefficients for the Padé approximant of appropriate order (Baker, 1975) <ISBN:9780120748556>.

This package provides the SELF criteria to learn causal structure. Please cite "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equational Embedded Likelihood Framework for Causal Discovery. AAAI. 2018.".

Accurately estimates phase shifts by accounting for period changes and for the point in the circadian cycle at which the stimulus occurs. See Tackenberg et al. (2018) <doi:10.1177/0748730418768116>.

This is a framework that aims to provide methods and tools for assessing the impact of different sources of uncertainties (e.g.positional uncertainty) on performance of species distribution models (SDMs).).

Handle climate data from the DWD ('Deutscher Wetterdienst', see <https://www.dwd.de/EN/climate_environment/cdc/cdc_node_en.html> for more information). Choose observational time series from meteorological stations with selectDWD()'. Find raster data from radar and interpolation according to <https://brry.github.io/rdwd/raster-data.html>. Download (multiple) data sets with progress bars and no re-downloads through dataDWD()'. Read both tabular observational data and binary gridded datasets with readDWD()'.

Detects copy number alteration events in targeted exon sequencing data for tumor samples without matched normal controls. The advantage of this method is that it can be applied to smaller sequencing panels including evaluations of exon, transcript, gene, or even user specified genetic regions of interest. Functions in the package include steps for GC-content correction, calculation of quantile based normal karyotype ranges, and calculation of feature score. Cutoffs for "normal" quantile and score are user-adjustable.

Test Statistics for Independence in High-Dimensional Datasets. This package consists of two functions to perform the complete independence test based on test statistics proposed by Bulut (unpublished yet) and suggested by Najarzadeh (2021) <doi: 10.1080/03610926.2019.1702699>. The Bulut's statistic is not sensitive to outliers in high-dimensional data, unlike one of Najarzadeh (2021) <doi: 10.1080/03610926.2019.1702699>. So, the Bulut's statistic can be performed robustly by using RDnp function.

This package provides reference classes implementing some useful data structures. The package implements these data structures by using the reference class R6. Therefore, the classes of the data structures are also reference classes which means that their instances are passed by reference. The implemented data structures include stack, queue, double-ended queue, doubly linked list, set, dictionary and binary search tree. See for example <https://en.wikipedia.org/wiki/Data_structure> for more information about the data structures.