Compared with the similar graph embedding method such as Laplacian Eigenmaps, Vicus can exploit more local structures of graph data. For the details of the methods, see the reference section of GitHub README.md <https://github.com/rikenbit/Vicus>.

This package provides tools to estimate the impact of vaccination campaigns at population level (number of events averted, number of avertable events, number needed to vaccinate). Inspired by the methodology proposed by Foppa et al. (2015) <doi:10.1016/j.vaccine.2015.02.042> and Machado et al. (2019) <doi:10.2807/1560-7917.ES.2019.24.45.1900268> for influenza vaccination impact.

This package provides a suite of plots for displaying variable importance and two-way variable interaction jointly. Can also display partial dependence plots laid out in a pairs plot or zenplots style.

Using frequency matrices, very low frequency variants (VLFs) are assessed for amino acid and nucleotide sequences. The VLFs are then compared to see if they occur in only one member of a species, singleton VLFs, or if they occur in multiple members of a species, shared VLFs. The amino acid and nucleotide VLFs are then compared to see if they are concordant with one another. Amino acid VLFs are also assessed to determine if they lead to a change in amino acid residue type, and potential changes to protein structures. Based on Stoeckle and Kerr (2012) <doi:10.1371/journal.pone.0043992> and Phillips et al. (2023) <doi:10.3897/BDJ.11.e96480>.

This package implements functions for varying coefficient meta-analysis methods. These methods do not assume effect size homogeneity. Subgroup effect size comparisons, general linear effect size contrasts, and linear models of effect sizes based on varying coefficient methods can be used to describe effect size heterogeneity. Varying coefficient meta-analysis methods do not require the unrealistic assumptions of the traditional fixed-effect and random-effects meta-analysis methods. For details see: Statistical Methods for Psychologists, Volume 5, <https://dgbonett.sites.ucsc.edu/>.

This package provides a set of basic tools to transform functions into functions with input validation checks, in a manner suitable for both programmatic and interactive use.

This package implements the Vine Copula Change Point (VCCP) methodology for the estimation of the number and location of multiple change points in the vine copula structure of multivariate time series. The method uses vine copulas, various state-of-the-art segmentation methods to identify multiple change points, and a likelihood ratio test or the stationary bootstrap for inference. The vine copulas allow for various forms of dependence between time series including tail, symmetric and asymmetric dependence. The functions have been extensively tested on simulated multivariate time series data and fMRI data. For details on the VCCP methodology, please see Xiong & Cribben (2021).

Various methods to count ballots in voting systems are provided. Functions to check validity of ballots are also provided to ensure flexibility.

This package provides variable selection for linear models and generalized linear models using Bayesian information criterion (BIC) and model posterior probability (MPP). Given a set of candidate predictors, it evaluates candidate models and returns model-level summaries (BIC and MPP) and predictor-level posterior inclusion probabilities (PIP). For more details see Xu, S., Ferreira, M. A., & Tegge, A. N. (2025) <doi:10.48550/arXiv.2510.02628>.

Historical results for the state of Virginia lottery draw games. Data were downloaded from https://www.valottery.com/.

This package implements an entropy-informed pipeline for detecting emerging variants in viral amino acid sequence data, extending prior clustering-based approaches including hemagglutinin clustering methods (Li et al., 2015) <doi:10.1142/9789814667944_0018>. Provides a fully vectorized FASTA preprocessing toolkit covering header parsing, two-pass date and country extraction, ambiguous-residue filtering, and integer encoding under a 25-symbol amino acid alphabet. Computes per-site Shannon entropy across user-defined cumulative, sliding, or disjoint temporal partitions and clusters per-site entropy values using Gaussian mixture models via mclust (Scrucca et al., 2016) <doi:10.32614/RJ-2016-021>. Quantifies temporal distributional shifts between partitions using the Hellinger distance (van der Vaart, 1998) <doi:10.1017/CBO9780511802256>, and detects temporal change points non-parametrically using energy statistics (Matteson and James, 2014) <doi:10.1080/01621459.2013.849605> via ecp or wild binary segmentation (Fryzlewicz, 2014) <doi:10.1214/14-AOS1245> via HDcpDetect'. Per-site amino-acid frequency tables and entropy trajectory plots characterize sequence composition and evolutionary dynamics across time. A configurable multi-variant simulation engine generates synthetic sequence time series with known ground truth for benchmarking detection pipelines. A curated dataset of SARS-CoV-2 Variants of Concern and Variants of Interest with associated lineage and surveillance metadata is included, along with a bundled National Center for Biotechnology Information (NCBI) Spike protein sample and vignettes demonstrating the full workflow.

This package implements the variable neighborhood trust region search (VNTRS) algorithm for nonlinear global optimization, following Bierlaire et al. (2009) "A Heuristic for Nonlinear Global Optimization" <doi:10.1287/ijoc.1090.0343>. The method combines neighborhood exploration with a trust-region framework to search the solution space efficiently. It can terminate a local search early when the iterates converge toward a previously visited local optimum or when further improvement within the current region is unlikely. The algorithm can also be used to identify multiple local optima.

This package provides a convenient interface for constructing plots to visualize the fit of regression models arising from a wide variety of models in R ('lm', glm', coxph', rlm', gam', locfit', lmer', randomForest', etc.).

An implementation of Vasicek and Song goodness-of-fit tests. Several functions are provided to estimate differential Shannon entropy, i.e., estimate Shannon entropy of real random variables with density, and test the goodness-of-fit of some family of distributions, including uniform, Gaussian, log-normal, exponential, gamma, Weibull, Pareto, Fisher, Laplace and beta distributions; see Lequesne and Regnault (2020) <doi:10.18637/jss.v096.c01>.

This package provides a programmatic interface in R for the US Department of Transportation (DOT) National Highway Transportation Safety Administration (NHTSA) vehicle identification number (VIN) API, located at <https://vpic.nhtsa.dot.gov/api/>. The API can decode up to 50 vehicle identification numbers in one call, and provides manufacturer information about the vehicles, including make, model, model year, and gross vehicle weight rating (GVWR).

This package implements wild bootstrap tests for autocorrelation in Vector Autoregressive (VAR) models based on Ahlgren and Catani (2016) <doi:10.1007/s00362-016-0744-0>, a combined Lagrange Multiplier (LM) test for Autoregressive Conditional Heteroskedasticity (ARCH) in VAR models from Catani and Ahlgren (2016) <doi:10.1016/j.ecosta.2016.10.006>, and bootstrap-based methods for determining the cointegration rank from Cavaliere, Rahbek, and Taylor (2012) <doi:10.3982/ECTA9099> and Cavaliere, Rahbek, and Taylor (2014) <doi:10.1080/07474938.2013.825175>.

This package provides access to data collected by the Ecuadorian Truth Commission. Allows users to extract and analyze systematized information for human rights research in Ecuador. The package contains datasets documenting human rights violations from 1984-2008, including victim information, violation types, perpetrators, and geographic distribution.

This package contains logic for cell-specific gene set scoring of single cell RNA sequencing data.

Generate suggestions for validation rules from a reference data set, which can be used as a starting point for domain specific rules to be checked with package validate'.

Video interactivity within shiny applications using video.js'. Enables the status of the video to be sent from the UI to the server, and allows events such as playing and pausing the video to be triggered from the server.

Time series decomposition for univariate time series using the "Verallgemeinerte Berliner Verfahren" (Generalized Berlin Method) as described in Kontinuierliche Messgröà en und Stichprobenstrategien in Raum und Zeit mit Anwendungen in den Natur-, Umwelt-, Wirtschafts- und Finanzwissenschaften', by Hebbel and Steuer, Springer Berlin Heidelberg, 2022 <doi:10.1007/978-3-662-65638-9>, or Decomposition of Time Series using the Generalised Berlin Method (VBV) by Hebbel and Steuer, in Jan Beran, Yuanhua Feng, Hartmut Hebbel (Eds.): Empirical Economic and Financial Research - Theory, Methods and Practice, Festschrift in Honour of Prof. Siegfried Heiler. Series: Advanced Studies in Theoretical and Applied Econometrics. Springer 2014, p. 9-40.

This package provides a wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient, stable, and high confidential variables from omics-based data. Using a bagging strategy in combination of a parametric method or inflection point search method for cut-off threshold determination. This package can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. Luo H, Zhao Q, et al (2020) <doi:10.1126/scitranslmed.aax7533> for more details.

Functionality for creating phase portraits of functions in the complex number plane. Works with R base graphics, whose full functionality is available. Parallel processing is used for optimum performance.

Debugging pipe chains often consists of viewing the output after each step. This package adds RStudio addins and two functions that allow outputing each or select steps in a convenient way.