An optimizer of Fused-Sparse Structural Equation Models, which is the state of the art jointly fused sparse maximum likelihood function for structural equation models proposed by Xin Zhou and Xiaodong Cai (2018 <doi:10.1101/466623>).

New kernel-based test and fast tests for detecting change-points or changed-intervals where the distributions abruptly change. They work well particularly for high-dimensional data. Song, H. and Chen, H. (2022) <arXiv:2206.01853>.

Mixtures of skewed and elliptical distributions are implemented using mixtures of multivariate skew power exponential and power exponential distributions, respectively. A generalized expectation-maximization framework is used for parameter estimation. See citation() for how to cite.

Data sets in the book entitled "Multivariate Statistical Methods with R Applications", H.Bulut (2018). The book was published in Turkish and the original name of this book will be "R Uygulamalari ile Cok Degiskenli Istatistiksel Yontemler".

This package provides tools for handling NetCDF metadata in data frames. The metadata is provided as relations in tabular form, to avoid having to scan printed header output or to navigate nested lists of raw metadata.

Perform flexible simulation studies using one or multiple computer cores. The package is set up to be usable on high-performance clusters in addition to being run locally, see examples on <https://github.com/SachaEpskamp/parSim>.

Homogeneity tests of the coefficients in panel data. Currently, only the Hsiao test for determining coefficient homogeneity between the panel data individuals is implemented, as described in Hsiao (2022), "Analysis of Panel Data" (<doi:10.1017/9781009057745>).

This package provides advanced functionality for performing configurational comparative research with Qualitative Comparative Analysis (QCA), including crisp-set, multi-value, and fuzzy-set QCA. It also offers advanced tools for sensitivity diagnostics and methodological evaluations of QCA.

This function aims to calculate risk of developing cardiovascular disease of individual patients in next 10 years. This unofficial package was based on published open-sourced free risk prediction algorithm QRISK3-2017 <https://qrisk.org/src.php>.

This package implements the SVM-Maj algorithm to train data with support vector machine <doi:10.1007/s11634-008-0020-9>. This algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.

Simultaneously infers state-dependent diversification across two or more states of a single or multiple traits while accounting for the role of a possible concealed trait. See Herrera-Alsina et al. (2019) <doi:10.1093/sysbio/syy057>.

Sequential Kalman filter for scalable online changepoint detection by temporally correlated data. It enables fast single and multiple change points with missing values. See the reference: Hanmo Li, Yuedong Wang, Mengyang Gu (2023), <arXiv:2310.18611>.

This package performs sparse discriminant analysis on a combination of node and leaf predictors when the predictor variables are structured according to a tree, as described in Fukuyama et al. (2017) <doi:10.1371/journal.pcbi.1005706>.

Measure text's sentiment with dictionaries and simple rules covering negations and modifiers. User-supplied dictionaries are supported, including Unicode emojis and multi-word tokens, so this package can also be used to study constructs beyond sentiment.

Implement text and sentiment analysis with texter'. Generate sentiment scores on text data and also visualize sentiments. texter allows you to quickly generate insights on your data. It includes support for lexicons such as NRC and Bing'.

Retrieve data from the UNESCO Institute for Statistics (UIS) API <https://api.uis.unesco.org/api/public/documentation/>. UIS provides public access to more than 4,000 indicators focusing on education, science and technology, culture, and communication.

This package provides unified syntax to write data from lazy dplyr tbl or dplyr sql query or a dataframe to a database table with modes such as create, append, insert, update, upsert, patch, delete, overwrite, overwrite_schema.

Setting layout through YAML headers in R-Markdown documents, enabling their automatic generation. Functions and methods may summarize R objects in automatic reports, for instance check-lists and further reports applied to the packages taxlist and vegtable'.

This package provides tools to estimate parameters of accumulated damage (load duration) models based on failure time data under a Bayesian framework, using Approximate Bayesian Computation (ABC), and to assess long-term reliability under stochastic load profiles.

This package provides an R wrapper of OpenAI API endpoints (see https://platform.openai.com/docs/introduction for details). This package covers Models, Completions, Chat, Edits, Images, Embeddings, Audio, Files, Fine-tunes, Moderations, and legacy Engines endpoints.

This package provides a toolset for Geometric Morphometrics and mesh processing. This includes (among other stuff) mesh deformations based on reference points, permutation tests, detection of outliers, processing of sliding semi-landmarks and semi-automated surface landmark placement.

This package provides a more scalable alternative to Venn and Euler diagrams for visualizing intersecting sets. Create visualizations of intersecting sets using a novel matrix design, along with visualizations of several common set, element and attribute related tasks.

This is a package for maximum likelihood estimation of random utility discrete choice models. The software is described in Croissant (2020) <doi:10.18637/jss.v095.i11> and the underlying methods in Train (2009) <doi:10.1017/CBO9780511805271>.

Supports calculations and visualization for renewable power systems and the environment. Analysis and graphical tools for DC and AC circuits and their use in electric power systems. Analysis and graphical tools for thermodynamic cycles and heat engines, supporting efficiency calculations in coal-fired power plants, gas-fired power plants. Calculations of carbon emissions and atmospheric CO2 dynamics. Analysis of power flow and demand for the grid, as well as power models for microgrids and off-grid systems. Provides resource and power generation for hydro power, wind power, and solar power.