This package provides a set of tools to foster the development of reproducible analytical workflow by simplifying the download of data and metadata from DataONE (<https://www.dataone.org>) and easily importing this information into R.

Classification, regression, and clustering with k nearest neighbors algorithm. Implements several distance and similarity measures, covering continuous and logical features. Outputs ranked neighbors. Most features of this package are directly based on the PMML specification for KNN.

Derives the most frequent hierarchies along with their probability of occurrence. One can also define complex hierarchy criteria and calculate their probability. Methodology based on Papakonstantinou et al. (2021) <DOI:10.21203/rs.3.rs-858140/v1>.

Download and import of OpenStreetMap ('OSM') data as sf or sp objects. OSM data are extracted from the Overpass web server (<https://overpass-api.de/>) and processed with very fast C++ routines for return to R'.

This package provides a tool, grammar, and standard to represent and exchange R package source code as text files. Converts one or more source packages to a text file and restores the package structures from the file.

This package provides a wrapper for Paddle - The Merchant of Record for digital products API (Application Programming Interface) <https://developer.paddle.com/api-reference/overview>. Provides functions to manage and analyze products, customers, invoices and many more.

Translating messages in R packages is managed using the po top-level directory and the gettext program. This package provides some helper functions for building this support in R packages, e.g. common validation & I/O tasks.

Probabilistic factor analysis for spatially-aware dimension reduction across multi-section spatial transcriptomics data with millions of spatial locations. More details can be referred to Wei Liu, et al. (2023) <doi:10.1101/2023.07.11.548486>.

This package provides a dataset of Pokemon information in both English and Brazilian Portuguese. The dataset contains 949 rows and 22 columns, including information such as the Pokemon's name, ID, height, weight, stats, type, and more.

Interactively play a game of sokoban ,which has nine game levels.Sokoban is a type of transport puzzle, in which the player pushes boxes or crates around in a warehouse, trying to get them to storage locations.

Fit a trio model via penalized maximum likelihood. The model is fit for a path of values of the penalty parameter. This package is based on Noah Simon, et al. (2011) <doi:10.1080/10618600.2012.681250>.

Verb-like functions to work with messy data, often derived from spreadsheets or parsed PDF tables. Includes functions for unwrapping values broken up across rows, relocating embedded grouping values, and to annotate meaningful formatting in spreadsheet files.

This package provides helpers for reordering factor levels (including moving specified levels to front, ordering by first appearance, reversing, and randomly shuffling), and tools for modifying factor levels (including collapsing rare levels into other, "anonymizing", and manually "recoding").

Maximum likelihood computations for Tweedie families, including the series expansion (Dunn and Smyth, 2005; <doi10.1007/s11222-005-4070-y>) and the Fourier inversion (Dunn and Smyth, 2008; <doi:10.1007/s11222-007-9039-6>), and related methods.

This package provides a reticulate wrapper for the Python package anndata. It provides a scalable way of keeping track of data and learned annotations. It is used to read from and write to the h5ad file format.

Rasterize only specific layers of a ggplot2 plot while simultaneously keeping all labels and text in vector format. This allows users to keep plots within the reasonable size limit without losing vector properties of the scale-sensitive information.

This package provides kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.

This package provides a new class Formula, which extends the base class formula. It supports extended formulas with multiple parts of regressors on the right-hand side and/or multiple responses on the left-hand side.

Reprotest builds the same source code twice in different environments, and then checks the binaries produced by each build for differences. If any are found, then diffoscope or diff is used to display them in detail for later analysis.

Classify hemispherical photographs of the plant canopy with algorithms specially developed for such a task and well documented in DÃ az and Lencinas (2015) <doi:10.1109/lgrs.2015.2425931> and DÃ az and Lencinas (2018) <doi:10.1139/cjfr-2018-0006>. It supports non-circular hemispherical photography, such as those acquired with 15mm lenses or with auxiliary fish-eye lenses attached to mobile devices. For smartphone-based hemispherical photography see DÃ az (2023) <doi:10.1111/2041-210x.14059>. Most of the functions also support restricted view photography.

This package provides a pair of functions for calculating mean residual life (MRL) , median residual life, and percentile residual life using the outputs of either the flexsurv package or parameters provided by the user. Input information about the distribution, the given life value, the percentile, and the type of residual life, and the function will return your desired values. For the flexsurv option, the function allows the user to input their own data for making predictions. This function is based on Jackson (2016) <doi:10.18637/jss.v070.i08>.

Non-parametric clustering of joint pattern multi-genetic/epigenetic factors. This package contains functions designed to cluster subjects based on gene features including single nucleotide polymorphisms (SNPs), DNA methylation (CPG), gene expression (GE), and covariate data. The novel concept follows the general K-means (Hartigan and Wong (1979) <doi:10.2307/2346830> framework but uses weighted Euclidean distances across the gene features to cluster subjects. This approach is unique in that it attempts to capture all pairwise interactions in an effort to cluster based on their complex biological interactions.

Compute spatially explicit land-use metrics for stream survey sites in GRASS GIS and R as an open-source implementation of IDW-PLUS (Inverse Distance Weighted Percent Land Use for Streams). The package includes functions for preprocessing digital elevation and streams data, and one function to compute all the spatially explicit land use metrics described in Peterson et al. (2011) <doi:10.1111/j.1365-2427.2010.02507.x> and previously implemented by Peterson and Pearse (2017) <doi:10.1111/1752-1688.12558> in ArcGIS-Python as IDW-PLUS.

Preprocessing tools and biodiversity measures (species abundance, species richness, population heterogeneity and sensitivity) for analysing marine benthic data. See Van Loon et al. (2015) <doi:10.1016/j.seares.2015.05.002> for an application of these tools.