Holistic generalized linear models (HGLMs) extend generalized linear models (GLMs) by enabling the possibility to add further constraints to the model. The holiglm package simplifies estimating HGLMs using convex optimization. Additional information about the package can be found in the reference manual, the README and the accompanying paper <doi:10.18637/jss.v108.i07>.

Synthesize images into characteristic features for time-series analysis or machine learning applications. The package was originally intended for monitoring volcanic eruptions in video data by highlighting and extracting regions above the vent associated with plume activity. However, the functions within are general and have wide applications for image processing, analyzing, filtering, and plotting.

Some functions for performing ICA, MICA, Group ICA, and Multilinear ICA are implemented. ICA, MICA/Group ICA, and Multilinear ICA extract statistically independent components from single matrix, multiple matrices, and single tensor, respectively. For the details of these methods, see the reference section of GitHub README.md <https://github.com/rikenbit/iTensor>.

Linear ridge regression coefficient's estimation and testing with different ridge related measures such as MSE, R-squared etc. REFERENCES i. Hoerl and Kennard (1970) <doi:10.1080/00401706.1970.10488634>, ii. Halawa and El-Bassiouni (2000) <doi:10.1080/00949650008812006>, iii. Imdadullah, Aslam, and Saima (2017), iv. Marquardt (1970) <doi:10.2307/1267205>.

Facilitates tidy calculation of popular quantitative marketing metrics. It also includes functions for doing analysis that will help marketers and data analysts better understand the drivers and/or trends of these metrics. These metrics include Customer Experience Index <https://go.forrester.com/analytics/cx-index/> and Net Promoter Score <https://www.netpromoter.com/know/>.

R Client for the Microsoft Cognitive Services Text-to-Speech REST API, including voice synthesis. A valid account must be registered at the Microsoft Cognitive Services website <https://azure.microsoft.com/en-us/products/ai-services/> in order to obtain a (free) API key. Without an API key, this package will not work properly.

This package contains a collection of datasets for working with machine learning tasks. It will contain datasets for supervised machine learning Jiang (2020)<doi:10.1016/j.beth.2020.05.002> and will include datasets for classification and regression. The aim of this package is to use data generated around health and other domains.

Picks the suitable cell types in spatial and scRNA-seq data using shrinkage methods. The package includes curated reference gene expression profiles for human and mouse cell types, facilitating immediate application to common spatial transcriptomics or scRNA datasets. Additionally, users can input custom reference data to support tissue- or experiment-specific analyses.

Calculate seat apportionment for legislative bodies with various methods. The algorithms include divisor or highest averages methods (e.g. Jefferson, Webster or Adams), largest remainder methods and biproportional apportionment. Gaffke, N. & Pukelsheim, F. (2008) <doi:10.1016/j.mathsocsci.2008.01.004> Oelbermann, K. F. (2016) <doi:10.1016/j.mathsocsci.2016.02.003>.

Survey to collect data about the social and economic conditions of Indonesian society. This activity aims to include: As a data source for planning and evaluating national, sectoral development programs, and providing indicators for Sustainable Development Goals (TPB), National Medium Term Development Plan (RPJMN), and Nawacita, GDP/GRDP and annual Integrated Institutional Balance Sheet.

This package provides a small POSIX sockets interface to R, enabling direct network communication from R for applications that need low-level socket control or lightweight client and server connections. This package provides IPv4 and IPv6 support with TCP/UDP protocols. It functional API with socket_create and an R6 interface through Socket object.

This package provides developer-focused helper functions and S3 classes to ease the creation of structured subtypes of data frames. Developers can require certain columns and types to be present, and can enforce crossing and nesting relationships between values in different columns. Type-specific metadata and attributes are preserved through common data frame manipulations.

This package provides a tidy workflow for generating, estimating, reporting, and plotting structural equation models using lavaan', OpenMx', or Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as tidy data, making them easy to customize. Includes functionality to estimate latent class analyses, and to plot dagitty and igraph objects.

Implementation of Time to Target plot based on the work of Ribeiro and Rosseti (2015) <DOI:10.1007/s11590-014-0760-8>, that describe a numerical method that gives the probability of an algorithm A finds a solution at least as good as a given target value in smaller computation time than algorithm B.

Download and read Brazilian Federal Highway Police ('PRF') open data on traffic accidents by person, by occurrence, and traffic violations <https://www.gov.br/prf/pt-br/acesso-a-informacao/dados-abertos/dados-abertos-da-prf>. Data are retrieved on demand as Parquet files distributed via GitHub releases and cached locally for reuse.

Construct and plot objective hierarchies and associated value and utility functions. Evaluate the values and utilities and visualize the results as colored objective hierarchies or tables. Visualize uncertainty by plotting median and quantile intervals within the nodes of objective hierarchies. Get numerical results of the evaluations in standard R data types for further processing.

This is a package for de novo identification and extraction of differentially methylated regions (DMRs) from the human genome using Whole Genome Bisulfite Sequencing (WGBS) and Illumina Infinium Array (450K and EPIC) data. It provides functionality for filtering probes possibly confounded by SNPs and cross-hybridisation. It includes GRanges generation and plotting functions.

The Spectra package defines an efficient infrastructure for storing and handling mass spectrometry spectra and functionality to subset, process, visualize and compare spectra data. It provides different implementations (backends) to store mass spectrometry data. These comprise backends tuned for fast data access and processing and backends for very large data sets ensuring a small memory footprint.

BiocSet displays different biological sets in a triple tibble format. These three tibbles are element, set, and elementset. The user has the ability to activate one of these three tibbles to perform common functions from the dplyr package. Mapping functionality and accessing web references for elements/sets are also available in BiocSet.

r-selectr translates a CSS3 selector into an equivalent XPath expression. This allows you to use CSS selectors when working with the XML package as it can only evaluate XPath expressions. Also provided are convenience functions useful for using CSS selectors on XML nodes. This package is a port of the Python package cssselect.

To make it easy to create CONSORT diagrams for the transparent reporting of participant allocation in randomized, controlled clinical trials. This is done by creating a standardized disposition data, and using this data as the source for the creation a standard CONSORT diagram. Human effort by supplying text labels on the node can also be achieved.

Stringr is a consistent, simple and easy to use set of wrappers around the fantastic stringi package. All function and argument names (and positions) are consistent, all functions deal with "NA"'s and zero length vectors in the same way, and the output from one function is easy to feed into the input of another.

This package provides functions for fitting phylogenetic linear models and phylogenetic generalized linear models. The computation uses an algorithm that is linear in the number of tips in the tree. The package also provides functions for simulating continuous or binary traits along the tree. Other tools include functions to test the adequacy of a population tree.

ibus-rime provides the Rime input method engine for IBus. Rime is a lightweight, extensible input method engine supporting various input schemas including glyph-based input methods, romanization-based input methods as well as those for Chinese dialects. It has the ability to compose phrases and sentences intelligently and provide very accurate traditional Chinese output.