This package provides a port of Ruby Warrior. Teaches R programming in a fun and interactive way.

Matrix reconstruction, also known as matrix completion, is the task of inferring missing entries of a partially observed matrix. This package provides a method called OptSpace, which was proposed by Keshavan, R.H., Oh, S., and Montanari, A. (2009) <doi:10.1109/ISIT.2009.5205567> for a case under low-rank assumption.

Parameter estimation, computation of probability, information, and (log-)likelihood, and visualization of item/test characteristic curves and item/test information functions for three uni-dimensional item response theory models: the 3-parameter-logistic model, generalized partial credit model, and graded response model. The full documentation and tutorials are at <https://github.com/xluo11/Rirt>.

We provide linear and nonlinear dimension reduction techniques. Intrinsic dimension estimation methods for exploratory analysis are also provided. For more details on the package, see the paper by You and Shung (2022) <doi:10.1016/j.simpa.2022.100414>.

This tool can be used to build binary interval trees using real number inputs. The tree supports queries of intervals overlapping a single number or an interval (start, end). Intervals with same bounds but different names are treated as distinct intervals. Insertion of intervals is also allowed. Deletion of intervals is not implemented at this point. See Mark de Berg, Otfried Cheong, Marc van Kreveld, Mark Overmars (2008). Computational Geometry: Algorithms and Applications, for a reference.

The Rcpp package contains a C++ library that facilitates the integration of R and C++ in various ways via a rich API. This API was preceded by an earlier version which has been deprecated since 2010 (but is still supported to provide backwards compatibility in the package RcppClassic'). This package RcppClassicExamples provides usage examples for the older, deprecated API. There is also a corresponding package RcppExamples with examples for the newer, current API which we strongly recommend as the basis for all new development.

Interface to SWI'-'Prolog', <https://www.swi-prolog.org/>. This package is normally not loaded directly, please refer to package rolog instead. The purpose of this package is to provide the Prolog runtime on systems that do not have a software installation of SWI'-'Prolog'.

Wrapper for widely used SUNDIALS software (SUite of Nonlinear and DIfferential/ALgebraic Equation Solvers) and more precisely to its CVODES solver. It is aiming to solve ordinary differential equations (ODE) and optionally pending forward sensitivity problem. The wrapper is made R friendly by allowing to pass custom parameters to user's callback functions. Such functions can be both written in R and in C++ ('RcppArmadillo flavor). In case of C++', performance is greatly improved so this option is highly advisable when performance matters. If provided, Jacobian matrix can be calculated either in dense or sparse format. In the latter case rmumps package is used to solve corresponding linear systems. Root finding and pending event management are optional and can be specified as R or C++ functions too. This makes them a very flexible tool for controlling the ODE system during the time course simulation. SUNDIALS library was published in Hindmarsh et al. (2005) <doi:10.1145/1089014.1089020>.

This package provides a resource represents some data or a computation unit. It is described by a URL and credentials. This package proposes a Resource model with "resolver" and "client" classes to facilitate the access and the usage of the resources.

Turns regression models inside out. Functions decompose variances and coefficients for various regression model types. Functions also visualize regression model objects using techniques developed in Schoon, Melamed, and Breiger (2024) <doi:10.1017/9781108887205>.

Enables the diagnostics and enhancement of regression model calibration.It offers both global and local visualization tools for calibration diagnostics and provides one recalibration method: Torres R, Nott DJ, Sisson SA, Rodrigues T, Reis JG, Rodrigues GS (2024) <doi:10.48550/arXiv.2403.05756>. The method leverages on Probabilistic Integral Transform (PIT) values to both evaluate and perform the calibration of statistical models. For a more detailed description of the package, please refer to the bachelor's thesis available bellow.

This package provides wrappers around base::grep() where the first argument is standardized to take the data object. This makes it less of a pain to use regular expressions with magrittr or other pipe operators.

The getconf command-line tool provided by libc allows querying of a large number of system variables. This package provides similar functionality.

R parallel implementation of Local Outlier Factor(LOF) which uses multiple CPUs to significantly speed up the LOF computation for large datasets. (Note: The overall performance depends on the computers especially the number of the cores).It also supports multiple k values to be calculated in parallel, as well as various distance measures in addition to the default Euclidean distance.

This package provides functions for (1) computing diagnostic test statistics (sensitivity, specificity, etc.) from confusion matrices with adjustment for various base rates or known prevalence based on McCaffrey et al (2003) <doi:10.1007/978-1-4615-0079-7_1>, (2) computing optimal cut-off scores with different criteria including maximizing sensitivity, maximizing specificity, and maximizing the Youden Index from Youden (1950) <doi:10.1002/1097-0142(1950)3:1%3C32::AID-CNCR2820030106%3E3.0.CO;2-3>, and (3) displaying and comparing classification statistics and area under the receiver operating characteristic (ROC) curves or area under the curves (AUC) across consecutive categories for ordinal variables.

Really Poor Man's Graphical User Interface, used to create interactive R analysis sessions with simple R commands.

The Randomized Trait Community Clustering method (Triado-Margarit et al., 2019, <doi:10.1038/s41396-019-0454-4>) is a statistical approach which allows to determine whether if an observed trait clustering pattern is related to an increasing environmental constrain. The method 1) determines whether exists or not a trait clustering on the sampled communities and 2) assess if the observed clustering signal is related or not to an increasing environmental constrain along an environmental gradient. Also, when the effect of the environmental gradient is not linear, allows to determine consistent thresholds on the community assembly based on trait-values.

This package provides a direct interface to the underlying XML representation of DDI Codebook 2.5 with flexible API creation.

This package provides a thin wrapper around the tiktoken-rs crate, allowing to encode text into Byte-Pair-Encoding (BPE) tokens and decode tokens back to text. This is useful to understand how Large Language Models (LLMs) perceive text.

This package provides fast procedures for exploring all pairs of cutpoints of a single covariate with respect to survival and determining optimal cutpoints using a hierarchical method and various ordered logrank tests.

According to the order of the loci on the chromosome, the loci can be connected according to the interrelationship between them and classified according to different locus types.

Computationally efficient tool for performing variable selection and obtaining robust estimates, which implements robust variable selection procedure proposed by Wang, X., Jiang, Y., Wang, S., Zhang, H. (2013) <doi:10.1080/01621459.2013.766613>. Users can enjoy the near optimal, consistent, and oracle properties of the procedures.

Inference for the treatment effect with possibly invalid instrumental variables via TSHT('Guo et al. (2016) <arXiv:1603.05224>) and SearchingSampling('Guo (2021) <arXiv:2104.06911>), which are effective for both low- and high-dimensional covariates and instrumental variables; test of endogeneity in high dimensions ('Guo et al. (2016) <arXiv:1609.06713>).

Focused on (but not exclusive to) data sets hosted on PhysioNet (<https://physionet.org>), ricu provides utilities for download, setup and access of intensive care unit (ICU) data sets. In addition to functions for running arbitrary queries against available data sets, a system for defining clinical concepts and encoding their representations in tabular ICU data is presented.