This package provides an implementation of a kernel-embedding of probability test for elliptical distribution. This is an asymptotic test for elliptical distribution under general alternatives, and the location and shape parameters are assumed to be unknown. Some side-products are posted, including the transformation between rectangular and polar coordinates and two product-type kernel functions. See Tang and Li (2024) <doi:10.48550/arXiv.2306.10594> for details.

Fits keyword assisted topic models (keyATM) using collapsed Gibbs samplers. The keyATM combines the latent dirichlet allocation (LDA) models with a small number of keywords selected by researchers in order to improve the interpretability and topic classification of the LDA. The keyATM can also incorporate covariates and directly model time trends. The keyATM is proposed in Eshima, Imai, and Sasaki (2024) <doi:10.1111/ajps.12779>.

This package provides a variable selection tool for multivariate normal variables with missing-at-random values using Bayesian Hierarchical Model. Visualization functions show the posterior distribution of gamma (inclusion variables) and beta (coefficients). Users can also visualize the heatmap of the posterior mean of covariance matrix. Kim, T. Nicolae, D. (2019) <https://github.com/tk382/MMVBVS/blob/master/workingpaper.pdf>. Guan, Y. Stephens, M. (2011) <doi:10.1214/11-AOAS455>.

Dealing with neutrosophic data in single valued form using score, accuracy and certainty functions to calculate ranks of Single Valued Neutrosophic Set (SVNS), also to calculate the Mann-Whitney test, and making a post-hoc test after rejecting the null hypothesis using the Neutrosophic Statistics Kruskal-Wallis test. For more information see Miari, Mahmoud; Anan, Mohamad Taher; Zeina, Mohamed Bisher(2022) <https://digitalrepository.unm.edu/nss_journal/vol51/iss1/60/>.

Plot the daily and cumulative number of downloads of your packages. It is designed to be slightly more convenient than the several similar programs. If you want to run this each morning, you do not need to keep typing in the names of your packages. Also, this combines the daily and cumulative counts in one run, you do not need to run separate programs to get both types of information.

Easily import the MI-SUVI data sets. The user can import data sets with full metrics, percentiles, Z-scores, or rankings. Data is available at both the County and Zip Code Tabulation Area (ZCTA) levels. This package also includes a function to import shape files for easy mapping and a function to access the full technical documentation. All data is sourced from the Michigan Department of Health and Human Services.

Calculates phenological cycle and anomalies using a non-parametric approach applied to time series of vegetation indices derived from remote sensing data or field measurements. The package implements basic and high-level functions for manipulating vector data (numerical series) and raster data (satellite derived products). Processing of very large raster files is supported. For more information, please check the following paper: Chávez et al. (2023) <doi:10.3390/rs15010073>.

This package provides functions to aid the identification of probable/possible duplicates in Plant Genetic Resources (PGR) collections using passport databases comprising of information records of each constituent sample. These include methods for cleaning the data, creation of a searchable Key Word in Context (KWIC) index of keywords associated with sample records and the identification of nearly identical records with similar information by fuzzy, phonetic and semantic matching of keywords.

It offers a wide variety of techniques, such as graphics, recoding, or regression models, for a comprehensive analysis of patient-reported outcomes (PRO). Especially novel is the broad range of regression models based on the beta-binomial distribution useful for analyzing binomial data with over-dispersion in cross-sectional, longitudinal, or multidimensional response studies (see Najera-Zuloaga J., Lee D.-J. and Arostegui I. (2019) <doi:10.1002/bimj.201700251>).

This package implements the copula-based estimator for univariate long-range dependent processes, introduced in Pumi et al. (2023) <doi:10.1007/s00362-023-01418-z>. Notably, this estimator is capable of handling missing data and has been shown to perform exceptionally well, even when up to 70% of data is missing (as reported in <arXiv:2303.04754>) and has been found to outperform several other commonly applied estimators.

Utilities for single nucleotide polymorphism (SNP) based kinship analysis testing and evaluation. The skater package contains functions for importing, parsing, and analyzing pedigree data, performing relationship degree inference, benchmarking relationship degree classification, and summarizing identity by descent (IBD) segment data. Package functions and methods are described in Turner et al. (2021) "skater: An R package for SNP-based Kinship Analysis, Testing, and Evaluation" <doi:10.1101/2021.07.21.453083>.

Stationary subspace analysis (SSA) is a blind source separation (BSS) variant where stationary components are separated from non-stationary components. Several SSA methods for multivariate time series are provided here (Flumian et al. (2021); Hara et al. (2010) <doi:10.1007/978-3-642-17537-4_52>) along with functions to simulate time series with time-varying variance and autocovariance (Patilea and Raissi(2014) <doi:10.1080/01621459.2014.884504>).

Sample size calculation to detect dynamic treatment regime (DTR) effects based on change in clinical attachment level (CAL) outcomes from a non-surgical chronic periodontitis treatments study. The experiment is performed under a Sequential Multiple Assignment Randomized Trial (SMART) design. The clustered tooth (sub-unit) level CAL outcomes are skewed, spatially-referenced, and non-randomly missing. The implemented algorithm is available in Xu et al. (2019+) <arXiv:1902.09386>.

Similarity regression, evaluating the probability of association between sets of ontological terms and binary response vector. A no-association model is compared with one in which the log odds of a true response is linked to the semantic similarity between terms and a latent characteristic ontological profile - Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases', Greene et al 2016 <doi:10.1016/j.ajhg.2016.01.008>.

The nature of working with structured query language ('SQL') scripts efficiently often requires the creation of temporary tables and there are few clean and simple R SQL execution approaches that allow you to complete this kind of work with the R environment. This package seeks to give SQL implementations in R a little love by deploying functions that allow you to deploy complex SQL scripts within a typical R workflow.

This package provides a simple approach for constructing dynamic materials modeling suggested by Prasad and Gegel (1984) <doi:10.1007/BF02664902>. It can easily generate various processing-maps based on this model as well. The calculation result in this package contains full materials constants, information about power dissipation efficiency factor, and rheological properties, can be exported completely also, through which further analysis and customized plots will be applicable as well.

Computes a point pattern in R^2 or on a graph that is representative of a collection of many data patterns. The result is an approximate barycenter (also known as Fréchet mean or prototype) based on a transport-transform metric. Possible choices include Optimal SubPattern Assignment (OSPA) and Spike Time metrics. Details can be found in Müller, Schuhmacher and Mateu (2020) <doi:10.1007/s11222-020-09932-y>.

Mixed type vectors are useful for combining semantically similar classes. Some examples of semantically related classes include time across different granularities (e.g. daily, monthly, annual) and probability distributions (e.g. Normal, Uniform, Poisson). These groups of vector types typically share common statistical operations which vary in results with the attributes of each vector. The vecvec data structure facilitates efficient storage and computation across multiple vectors within the same object.

This package provides Ion Trap positive ionization mode data in mzML file format. It includes a subset from 500-850 m/z and 1190-1310 seconds, including MS2 and MS3, intensity threshold 100.000; extracts from FTICR Apex III, m/z 400-450; a subset of UPLC - Bruker micrOTOFq data, both mzML and mz5; LC-MSMS and MRM files from proteomics experiments; and PSI mzIdentML example files for various search engines.

Network Common Data Form (netCDF) files are widely used for scientific data. Library-level access in R is provided through packages RNetCDF and ncdf4. The package ncdfCF is built on top of RNetCDF and makes the data and its attributes available as a set of R6 classes that are informed by the Climate and Forecasting Metadata Conventions. Access to the data uses standard R subsetting operators and common function forms.

Enables researchers to sample redistricting plans from a pre-specified target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo algorithms. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. Tools for analysis such as computation of various summary statistics and plotting functionality are also included. The package implements the SMC algorithm of McCartan and Imai (2023) <doi:10.1214/23-AOAS1763>, the enumeration algorithm of Fifield, Imai, Kawahara, and Kenny (2020) <doi:10.1080/2330443X.2020.1791773>, the Flip MCMC algorithm of Fifield, Higgins, Imai and Tarr (2020) <doi:10.1080/10618600.2020.1739532>, the Merge-split/Recombination algorithms of Carter et al. (2019) <doi:10.48550/arXiv.1911.01503> and DeFord et al. (2021) <doi:10.1162/99608f92.eb30390f>, and the Short-burst optimization algorithm of Cannon et al. (2020) <doi:10.48550/arXiv.2011.02288>.

Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM.

This R package offers block Gibbs samplers for the Bayesian (adaptive) graphical lasso, ridge, and naive elastic net priors. These samplers facilitate the simulation of the posterior distribution of precision matrices for Gaussian distributed data and were originally proposed by: Wang (2012) <doi:10.1214/12-BA729>; Smith et al. (2022) <doi:10.48550/arXiv.2210.16290> and Smith et al. (2023) <doi:10.48550/arXiv.2306.14199>, respectively.

Statistical tests for the comparison between two or more alpha coefficients based on either dependent or independent groups of individuals. A web interface is available at http://comparingcronbachalphas.org. A plugin for the R GUI and IDE RKWard is included. Please install RKWard from https:// rkward.kde.org to use this feature. The respective R package rkward cannot be installed directly from a repository, as it is a part of RKWard.