An implementation of the National Information Platforms for Nutrition or NiPN's analytic methods for assessing quality of anthropometric datasets that include measurements of weight, height or length, middle upper arm circumference, sex and age. The focus is on anthropometric status but many of the presented methods could be applied to other variables.

This package provides a set of techniques that can be used to develop, validate, and implement automated classifiers. A powerful tool for transforming raw data into meaningful information, ncodeR (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is designed specifically for working with big data: large document collections, logfiles, and other text data.

This package provides a small package designed for interpreting continuous and categorical latent variables. You provide a data set with a latent variable you want to understand and some other explanatory variables. It provides a description of the latent variable based on the explanatory variables. It also provides a name to the latent variable.

Collection of pivotal algorithms for: relabelling the MCMC chains in order to undo the label switching problem in Bayesian mixture models; fitting sparse finite mixtures; initializing the centers of the classical k-means algorithm in order to obtain a better clustering solution. For further details see Egidi, Pappadà , Pauli and Torelli (2018b)<ISBN:9788891910233>.

Allows to download current and historical METAR weather reports extract and parse basic parameters and present main weather information. Current reports are downloaded from Aviation Weather Center <https://aviationweather.gov/data/metar/> and historical reports from Iowa Environmental Mesonet web page of Iowa State University ASOS-AWOS-METAR <http://mesonet.agron.iastate.edu/AWOS/>.

Fits univariate Bayesian spatial regression models for large datasets using Nearest Neighbor Gaussian Processes (NNGP) detailed in Finley, Datta, Banerjee (2022) <doi:10.18637/jss.v103.i05>, Finley, Datta, Cook, Morton, Andersen, and Banerjee (2019) <doi:10.1080/10618600.2018.1537924>, and Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091>.

Create and format tables and APA statistics for scientific publication. This includes making a Table 1 to summarize demographics across groups, correlation tables with significance indicated by stars, and extracting formatted statistical summarizes from simple tests for in-text notation. The package also includes functions for Winsorizing data based on a Z-statistic cutoff.

Ordinary and modified statistics for symmetrical linear regression models with small samples. The supported ordinary statistics include Wald, score, likelihood ratio and gradient. The modified statistics include score, likelihood ratio and gradient. Diagnostic tools associated with the fitted model are implemented. For more details see Medeiros and Ferrari (2017) <DOI:10.1111/stan.12107>.

This package implements spatial and spatiotemporal GLMMs (Generalized Linear Mixed Effect Models) using TMB', fmesher', and the SPDE (Stochastic Partial Differential Equation) Gaussian Markov random field approximation to Gaussian random fields. One common application is for spatially explicit species distribution models (SDMs). See Anderson et al. (2024) <doi:10.1101/2022.03.24.485545>.

R functions are not supposed to print text without giving the user the option to turn the printing off or on using a Boolean verbose in a construct like if(verbose) print(...)'. But this black/white approach is rather rigid, and an approach with shades of gray might be more appropriate in many circumstances.

This package annmap provides annotation mappings for Affymetrix exon arrays and coordinate based queries to support deep sequencing data analysis. Database access is hidden behind the API which provides a set of functions such as genesInRange(), geneToExon(), exonDetails(), etc. Functions to plot gene architecture and BAM file data are also provided.

This package provides functions for fitting the generalized additive models for location scale and shape introduced by Rigby and Stasinopoulos (2005), doi:10.1111/j.1467-9876.2005.00510.x. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.

Statistical distribution in OOP (Object Oriented Programming) way. This package proposes a R6 class interface to classic statistical distribution, and new distributions can be easily added with the class AbstractDist. A useful point is the generic fit() method for each class, which uses a maximum likelihood estimation to find the parameters of a dataset, see, e.g. Hastie, T. and al (2009) <isbn:978-0-387-84857-0>. Furthermore, the rv_histogram class gives a non-parametric fit, with the same accessors that for the classic distribution. Finally, three random generators useful to build synthetic data are given: a multivariate normal generator, an orthogonal matrix generator, and a symmetric positive definite matrix generator, see Mezzadri, F. (2007) <arXiv:math-ph/0609050>.

This package provides direct access to the ALFRED (<https://alfred.stlouisfed.org>) and FRED (<https://fred.stlouisfed.org>) databases. Its functions return tidy data frames for different releases of the specified time series. Note that this product uses the FRED© API but is not endorsed or certified by the Federal Reserve Bank of St. Louis.

Multicenter randomized trials involve the collection and analysis of data from numerous study participants across multiple sites. Outliers may be present. To identify outliers, this package examines data at the individual level (univariate and multivariate) and site-level (with and without covariate adjustment). Methods are outlined in further detail in Rigdon et al (to appear).

This package provides a new class of Bayesian meta-analysis models that incorporates a model for internal and external validity bias. In this way, it is possible to combine studies of diverse quality and different types. For example, we can combine the results of randomized control trials (RCTs) with the results of observational studies (OS).

Semiparametric estimation for censored time series with lower detection limit. The latent response is a sequence of stationary process with Markov property of order one. Estimation of copula parameter(COPC) and Conditional quantile estimation are included for five available copula functions. Copula selection methods based on L2 distance from empirical copula function are also included.

An implementation of the probability mass function, cumulative density function, quantile function, random number generator, maximum likelihood estimator, and p-value generator from a conditional hypergeometric distribution: the distribution of how many items are in the overlap of all samples when samples of arbitrary size are each taken without replacement from populations of arbitrary size.

Categorize links and nodes from multiple networks in 3 categories: Common links (alpha) specific links (gamma), and different links (beta). Also categorizes the links into sub-categories and groups. The package includes a visualization tool for the networks. More information about the methodology can be found at: Gysi et. al., 2018 <arXiv:1802.00828>.

This package provides functions for visualizing, animating, solving and analyzing the Rubik's cube. Includes data structures for solvable and unsolvable cubes, random moves and random state scrambles and cubes, 3D displays and animations using OpenGL', patterned cube generation, and lightweight solvers. See Rokicki, T. (2008) <arXiv:0803.3435> for the Kociemba solver.

Create D3 based SVG ('Scalable Vector Graphics') graphics using a simple R API. The package aims to simplify the creation of many SVG plot types using a straightforward R API. The package relies on the r2d3 R package and the D3 JavaScript library. See <https://rstudio.github.io/r2d3/> and <https://d3js.org/> respectively.

This package provides simple functions to create constraints for small test assembly problems (e.g. van der Linden (2005, ISBN: 978-0-387-29054-6)) using sparse matrices. Currently, GLPK', lpSolve', Symphony', and Gurobi are supported as solvers. The gurobi package is not available from any mainstream repository; see <https://www.gurobi.com/downloads/>.

This package provides efficient methods to compute local and genome wide genetic distances (corresponding to the so called Hudson Fst parameters) through moment method, perform chromosome segmentation into homogeneous Fst genomic regions, and selection sweep detection for multi-population comparison. When multiple profile segmentation is required, the procedure can be parallelized using the future package.

Calculates various intraclass correlation coefficients used to quantify inter-rater and intra-rater reliability. The assumption here is that the raters produced quantitative ratings. Most of the statistical procedures implemented in this package are described in details in Gwet, K.L. (2014, ISBN:978-0970806284): "Handbook of Inter-Rater Reliability," 4th edition, Advanced Analytics, LLC.