Interactive shiny application for running Item Response Theory analysis. Provides graphics for characteristic and information curves.
Interface to JSON-stat <https://json-stat.org/>, a simple lightweight JSON format for data dissemination.
Information of the centroids and geographical limits of the regions, departments, provinces and districts of Peru.
This package provides a-priori, post-hoc, and compromise power-analyses for structural equation models (SEM).
Tidying functions built on data.table to provide quick and efficient data manipulation with minimal overhead.
Create HTML5 slides with R Markdown and the JavaScript library remark.js (<https://remarkjs.com>).
This package provides a wrapper for the Intro.js library. This package makes it easy to include step-by-step introductions, and clickable hints in a Shiny application. It supports both static introductions in the UI, and programmatic introductions from the server-side.
RcppDist provides a header-only C++ library with functions for additional statistical distributions that can be called from C++ when writing code using Rcpp or RcppArmadillo. Functions are available that return a NumericVector as well as doubles, and for multivariate or matrix distributions, Armadillo vectors and matrices.
Remedying proportional hazards assumption violations of a Cox proportional hazards model using stepwise split-point and time-varying coefficient methods based on Cox (1972) <doi:10.1111/j.2517-6161.1972.tb00899.x> and Klein and Moeschberger (1997) <doi:10.1007/978-1-4757-2728-9>.
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.
This package provides tools to read various file types into one list of data structures, usually, but not limited to, data frames. Excel files are read sheet-wise, i.e., all or a selection of sheets can be read. Field delimiters and decimal separators are determined automatically.
External jars required for package RMOA. RMOA is a framework to build data stream models on top of MOA (Massive Online Analysis - <https://moa.cms.waikato.ac.nz/>). The jar files are put in this R package, the modelling logic can be found in the RMOA package.
This package provides a simple and efficient way to read data from Paradox database files (.db) directly into R as modern tibble data frames. It uses the underlying pxlib C library to handle the low-level file format details and provides a clean, user-friendly R interface.
This package provides tools for creating, manipulating and reading Research Object Crates (RO-Crates), a lightweight approach to packaging research data with structured metadata. Includes utilities for metadata generation, entity management, validation and reading existing RO-Crates following the specification <https://w3id.org/ro/crate/1.2/>.
This package performs Wavelet Lifting Transforms focusing on signal denoising and functional data analysis (FDA). Implements a hybrid architecture with a zero-allocation C++ core for high-performance processing. Features include unified offline (batch) denoising, causal (real-time) filtering using a ring buffer engine, and adaptive recursive thresholding.
This package contains an extension library for accessing Redis database servers using the hiredis C library API.
This package provides infrastructure shared by all Biostrings-based genome data packages and support for efficient SNP representation.
This package provides Affymetrix Human Genome U95 Set annotation data (hgu95av2) assembled using data from public data repositories.
This package provides functions to fit nonparametric survival curves, plot them, and perform logrank or Wilcoxon type tests.
This package provides R miscellaneous utilities for basic data manipulation, debugging, visualization, lsf management, and common mskilab tasks.
This package creates alluvial diagrams (also known as parallel sets plots) for multivariate and time series-like data.
This package provides an easy way to fill an environment with active bindings that call a C++ function.
This package provides model-robust standard error estimators for cross-sectional, time series, clustered, panel, and longitudinal data.
This package provides selected commonly used methods for choosing univariate class intervals for mapping or other graphics purposes.