Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 667 packages in 0.13 seconds

BayesCVI — by Onthada Preedasawakul, 10 months ago

Bayesian Cluster Validity Index

Algorithms for computing and generating plots with and without error bars for Bayesian cluster validity index (BCVI) (O. Preedasawakul, and N. Wiroonsri, A Bayesian Cluster Validity Index, Computational Statistics & Data Analysis, 202, 108053, 2025. ) based on several underlying cluster validity indexes (CVIs) including Calinski-Harabasz, Chou-Su-Lai, Davies-Bouldin, Dunn, Pakhira-Bandyopadhyay-Maulik, Point biserial correlation, the score function, Starczewski, and Wiroonsri indices for hard clustering, and Correlation Cluster Validity, the generalized C, HF, KWON, KWON2, Modified Pakhira-Bandyopadhyay-Maulik, Pakhira-Bandyopadhyay-Maulik, Tang, Wiroonsri-Preedasawakul, Wu-Li, and Xie-Beni indices for soft clustering. The package is compatible with K-means, fuzzy C means, EM clustering, and hierarchical clustering (single, average, and complete linkage). Though BCVI is compatible with any underlying existing CVIs, we recommend users to use either WI or WP as the underlying CVI.

sparseIndexTracking — by Daniel P. Palomar, 7 years ago

Design of Portfolio of Stocks to Track an Index

Computation of sparse portfolios for financial index tracking, i.e., joint selection of a subset of the assets that compose the index and computation of their relative weights (capital allocation). The level of sparsity of the portfolios, i.e., the number of selected assets, is controlled through a regularization parameter. Different tracking measures are available, namely, the empirical tracking error (ETE), downside risk (DR), Huber empirical tracking error (HETE), and Huber downside risk (HDR). See vignette for a detailed documentation and comparison, with several illustrative examples. The package is based on the paper: K. Benidis, Y. Feng, and D. P. Palomar, "Sparse Portfolios for High-Dimensional Financial Index Tracking," IEEE Trans. on Signal Processing, vol. 66, no. 1, pp. 155-170, Jan. 2018. .

DBCVindex — by Davide Chicco, 4 months ago

Calculates the Density-Based Clustering Validation (DBCV) Index

A metric called 'Density-Based Clustering Validation index' (DBCV) index to evaluate clustering results, following the < https://github.com/pajaskowiak/clusterConfusion/blob/main/R/dbcv.R> 'R' implementation by Pablo Andretta Jaskowiak. Original 'DBCV' index article: Moulavi, D., Jaskowiak, P. A., Campello, R. J., Zimek, A., and Sander, J. (April 2014), "Density-based clustering validation", Proceedings of SDM 2014 -- the 2014 SIAM International Conference on Data Mining (pp. 839-847), . A more recent article on the 'DBCV' index: Chicco, D., Sabino, G.; Oneto, L.; Jurman, G. (August 2025), "The DBCV index is more informative than DCSI, CDbw, and VIASCKDE indices for unsupervised clustering internal assessment of concave-shaped and density-based clusters", PeerJ Computer Science 11:e3095 (pp. 1-), .

turner — by Frederic Bertrand, 8 months ago

Turn Vectors and Lists of Vectors into Indexed Structures

Package designed for working with vectors and lists of vectors, mainly for turning them into other indexed data structures.

seasonalytics — by Mr. Ankit Kumar Singh, 5 months ago

Compute Seasonality Index, Seasonalized and Deseaonalised the Time Series Data

The computation of a seasonal index is a fundamental step in time-series forecasting when the data exhibits seasonality. Specifically, a seasonal index quantifies — for each season (e.g. month, quarter, week) — the relative magnitude of the seasonal effect compared to the overall average level of the series. This package has been developed to compute seasonal index for time series data and it also seasonalise and desesaonalise the time series data.

ActivityIndex — by Jiawei Bai, 5 years ago

Activity Index Calculation using Raw 'Accelerometry' Data

Reads raw 'accelerometry' from 'GT3X+' data and plain table data to calculate Activity Index from 'Bai et al.' (2016) . The Activity Index refers to the square root of the second-level average variance of the three 'accelerometry' axes.

pim — by Joris Meys, a year ago

Fit Probabilistic Index Models

Fit a probabilistic index model as described in Thas et al, 2012: . The interface to the modeling function has changed in this new version. The old version is still available at R-Forge.

PSRICalc — by Richard Feiss, 6 months ago

Plant Stress Response Index Calculator

Calculate Plant Stress Response Index (PSRI) from time-series germination data with optional radicle vigor integration. Built on the methodological foundation of the Osmotic Stress Response Index (OSRI) framework developed by Walne et al. (2020) . Provides clean, direct PSRI calculations suitable for agricultural research and statistical analysis. Note: This package implements methodology currently under peer review. Please contact the author before publication using this approach.

openNCAI — by Kate O'Hara, 3 days ago

Calculates a Natural Capital Assets Index

Calculates a regional natural capital assets index (NCAI) following the methodology designed by NatureScot for Scotland as described in Albon, Balana, Brooker & Eastwood (2014) < https://www.nature.scot/sites/default/files/2025-06/naturescot-commissioned-report-751.pdf> and McKenna et al. (2019) . Processes habitat extent and condition data alongside metadata and weighting systems to produce a yearly single figure indexed relative to a base-year value of 100.

aieconindex — by Charles Coverdale, 2 days ago

Access the 'Anthropic Economic Index' Dataset

Provides clean, tidy access to the 'Anthropic Economic Index' (AEI) dataset hosted on 'Hugging Face' < https://huggingface.co/datasets/Anthropic/EconomicIndex>. The AEI is a recurring release from 'Anthropic' that maps usage of the 'Claude' family of large language models to occupations and tasks using the 'O*NET' taxonomy and the 'Standard Occupational Classification' system, following the methodology of Handa et al. (2025) and the privacy-preserving system 'Clio' of Tamkin et al. (2024) . Functions list available releases, fetch raw and enriched usage tables, retrieve task statements, request hierarchies, and country-level breakdowns, compare two releases, join the index to user-supplied data on a shared key, and compute usage-concentration metrics (Herfindahl-Hirschman Index, top-N concentration ratios, Shannon entropy). Data is cached locally for subsequent calls. Reproducibility helpers produce 'BibTeX' or plain-text citations that include the methodological source paper. This product uses the 'Anthropic Economic Index' data (released under CC-BY by 'Anthropic') but is not endorsed or certified by 'Anthropic'.