Generates Realizations of First-Order Integer Valued Autoregressive Processes with Zero-Inflated Innovations (ZINAR(1)) and Estimates its Parameters as described in Garay et al. (2021) <doi:10.1007/978-3-030-82110-4_2>.
This package provides tools for handling and analysing spherical data on a HEALPix grid, with applications to cosmic microwave background maps. Supports reading FITS files, converting between spherical and Cartesian coordinates and HEALPix ordering schemes, selecting sky regions, sampling pixels, and visualising maps. Implements empirical covariance, correlation and variogram estimation, covariance model fitting, angular power spectrum estimation, and distributional and entropy-based comparisons of spherical data. The package and its methods are described by Fryer, Li and Olenko (2020) <doi:10.32614/RJ-2020-012>.
Risk-related information (like the prevalence of conditions, the sensitivity and specificity of diagnostic tests, or the effectiveness of interventions or treatments) can be expressed in terms of frequencies or probabilities. By providing a toolbox of corresponding metrics and representations, riskyr computes, translates, and visualizes risk-related information in a variety of ways. Adopting multiple complementary perspectives provides insights into the interplay between key parameters and renders teaching and training programs on risk literacy more transparent (see <doi:10.3389/fpsyg.2020.567817>, for details).
This package implements the RecMap MP2 construction heuristic <doi:10.1109/INFVIS.2004.57>. This algorithm draws maps according to a given statistical value, e.g., election results, population, or epidemiological data. The basic idea of the RecMap algorithm is that each map region, e.g., different countries, is represented by a rectangle. The area of each rectangle represents the statistical value provided as input to maintain zero cartographic error. Computationally intensive tasks are implemented in C++. The included vignette documents recmap algorithm usage.
Empirical orthogonal teleconnections in R. remote is short for R(-based) EMpirical Orthogonal TEleconnections'. It implements a collection of functions to facilitate empirical orthogonal teleconnection analysis. Empirical Orthogonal Teleconnections (EOTs) denote a regression based approach to decompose spatio-temporal fields into a set of independent orthogonal patterns. They are quite similar to Empirical Orthogonal Functions (EOFs) with EOTs producing less abstract results. In contrast to EOFs, which are orthogonal in both space and time, EOT analysis produces patterns that are orthogonal in either space or time.
This is a package for semi-supervised isoform detection and annotation from both bulk and single-cell long read RNA-seq data. Flames provides automated pipelines for analysing isoforms, as well as intermediate functions for manual execution.
This package provides an API for efficient .hic file data extraction with programmatic matrix access. It doesn't store the pointer data for all the matrices, only the one queried, and currently it only supports matrices.
PrInCE (Predicting Interactomes from Co-Elution) uses a naive Bayes classifier trained on dataset-derived features to recover protein-protein interactions from co-elution chromatogram profiles. This package contains the R implementation of PrInCE.
Build and control interactive 2D and 3D maps with R/Shiny'. Lean set of powerful commands wrapping native calls to AMap <https://lbs.amap.com/api/jsapi-v2/summary/>. Deliver rich mapping functionality with minimal overhead.
Computes CRC32', CRC32C and CRC64NVME checksums using the aws-checksums library from the AWS Common Runtime, with runtime dispatch to hardware instructions ('SSE4.2', PCLMULQDQ', AVX-512', ARMv8 CRC and PMULL') and a portable software fallback.
Process Digital Cover Photography images of tree canopies to get canopy attributes like Foliage Cover and Leaf Area Index. Detailed description of the methods in Chianucci et al. (2022) <doi:10.1007/s00468-018-1666-3>.
Convex Clustering methods, including K-means algorithm, On-line Update algorithm (Hard Competitive Learning) and Neural Gas algorithm (Soft Competitive Learning), and calculation of several indexes for finding the number of clusters in a data set.
Datasets and functions to accompany the book Analisis de datos con el programa estadistico R: una introduccion aplicada by Salas-Eljatib (2021, ISBN: 9789566086109). The package helps carry out data management, exploratory analyses, and model fitting.
Decodes meshes and point cloud data encoded by the Draco mesh compression library from Google. Note that this is only designed for basic decoding and not intended as a full scale wrapping of the Draco library.
Visualize one-factor data frame. Beads plot consists of diamonds of each factor of each data series. A diamond indicates average and range. Look over a data frame with many numeric columns and a factor column.
Work with data on Venetian doges and dogaresse and the noble families of the Republic of Venice, and use it for social network analysis, as used in Merelo (2022) <doi:10.48550/arXiv.2209.07334>.
This package implements a fast, flexible method for simulating continuous variables with specified rank correlations using the Imanâ Conover transformation (Iman & Conover, 1982 <doi:10.1080/03610918208812265>) and back-ranking. Includes plotting tools and error-diagnostics.
Fits Weibull or sigmoidal models to percent loss conductivity (plc) curves as a function of plant water potential, computes confidence intervals of parameter estimates and predictions with bootstrap or parametric methods, and provides convenient plotting methods.
This package implements several extensions of the elastic net regularization scheme. These extensions include individual feature penalties for the L1 term, feature-feature penalties for the L2 term, as well as translation coefficients for the latter.
This package provides a plain Rcpp wrapper for MeCab that can segment Chinese, Japanese, and Korean text into tokens. The main goal of this package is to provide an alternative to tidytext using morphological analysis.
This package provides utility functions for, and drawing on, the data.table package. The package also collates useful miscellaneous functions extending base R not available elsewhere. The name is a portmanteau of utils and the author.
Uses the Jaccard similarity index to account for population structure in sequencing studies. This method was specifically designed to detect population stratification based on rare variants, hence it will be especially useful in rare variant analysis.
This package provides tools for generating an artificial population based on a kNN-based approximation to the approximate Bayesian bootstrap (KBAABB). This methodology is described in White et al. (2025) <doi:10.1093/forestry/cpaf071>.
This package provides a new practical method to evaluate whether relationships between two sets of high-dimensional variables are different or not across two conditions. Song, H. and Wu, M.C. (2023) <arXiv:2307.15268>.