Enhances the R Optimization Infrastructure ('ROI') package with the Embedded Conic Solver ('ECOS') for solving conic optimization problems.

The routine twosample_test() in this package runs the two sample test using various test statistic. The p values are found via permutation or large sample theory. The routine twosample_power() allows the calculation of the power in various cases, and plot_power() draws the corresponding power graphs. The routine run.studies allows a user to quickly study the power of a new method and how it compares to some of the standard ones.

MCMC based sampling of binary matrices with fixed margins as used in exact Rasch model tests.

The analysis of different aspects of biodiversity requires specific algorithms. For example, in regionalisation analyses, the high frequency of ties and zero values in dissimilarity matrices produced by Beta-diversity turnover produces hierarchical cluster dendrograms whose topology and bootstrap supports are affected by the order of rows in the original matrix. Moreover, visualisation of biogeographical regionalisation can be facilitated by a combination of hierarchical clustering and multi-dimensional scaling. The recluster package provides robust techniques to visualise and analyse patterns of biodiversity and to improve occurrence data for cryptic taxa.

Rapidly estimates tree-topology from large allele frequency data using Root Distances Method, under a Brownian Motion Model. See Peng et al. (2021) <doi:10.1016/j.ympev.2021.107142>.

OpenRefine (formerly Google Refine') is a popular, open source data cleaning software. This package enables users to programmatically trigger data transfer between R and OpenRefine'. Available functionality includes project import, export and deletion.

Automatic coding of open-ended responses to the Cognitive Reflection Test (CRT), a widely used class of tests in cognitive science and psychology that assess the tendency to override an initial intuitive (but incorrect) answer and engage in reflection to reach a correct solution. The package standardizes CRT response coding across datasets in cognitive psychology, decision-making, and related fields. Automated coding reduces manual effort and improves reproducibility by limiting variability from subjective interpretation of open-ended responses. The package supports automatic coding and machine scoring for the original English-language CRT (Frederick, 2005) <doi:10.1257/089533005775196732>, CRT4 and CRT7 (Toplak et al., 2014) <doi:10.1080/13546783.2013.844729>, CRT-long (Primi et al., 2016) <doi:10.1002/bdm.1883>, and CRT-2 (Thomson & Oppenheimer, 2016) <doi:10.1017/s1930297500007622>.

Fit (exponential or diffusion) response-time extended multinomial processing tree (RT-MPT) models by Klauer and Kellen (2018) <doi:10.1016/j.jmp.2017.12.003> and Klauer, Hartmann, and Meyer-Grant (submitted). The RT-MPT class not only incorporate frequencies like traditional multinomial processing tree (MPT) models, but also latencies. This enables it to estimate process completion times and encoding plus motor execution times next to the process probabilities of traditional MPTs. rtmpt is a hierarchical Bayesian framework and posterior samples are sampled using a Metropolis-within-Gibbs sampler (for exponential RT-MPTs) or Hamiltonian-within-Gibbs sampler (for diffusion RT-MPTs).

This package provides a collection of tools for measuring the similarity of text messages and tracing the flow of messages over time and across media.

This package provides a colour list and colour metric based on the ISCC-NBS System of Color Designation for use with the roloc package for converting colour specifications to colour names.

Visualize the objects in orbits in 2D and 3D. The packages is under developing to plot the orbits of objects in polar coordinate system. See the examples in demo.

This package provides a pure R implementation of the median cut algorithm. Extracts the dominant colors from an image, and turns them into a scale for use in plots or for fun!

For a multisite replication project, computes the consistency metric P_orig, which is the probability that the original study would observe an estimated effect size as extreme or more extreme than it actually did, if in fact the original study were statistically consistent with the replications. Other recommended metrics are: (1) the probability of a true effect of scientifically meaningful size in the same direction as the estimate the original study; and (2) the probability of a true effect of meaningful size in the direction opposite the original study's estimate. These two can be computed using the package \codeMetaUtility::prop_stronger. Additionally computes older metrics used in replication projects (namely expected agreement in "statistical significance" between an original study and replication studies as well as prediction intervals for the replication estimates). See Mathur and VanderWeele (under review; <https://osf.io/apnjk/>) for details.

SyncroSim is a generalized framework for managing scenario-based datasets (<https://syncrosim.com/>). rsyncrosim provides an interface to SyncroSim'. Simulation models can be added to SyncroSim in order to transform these datasets, taking advantage of general features such as defining scenarios of model inputs, running Monte Carlo simulations, and summarizing model outputs. rsyncrosim requires SyncroSim 2.3.5 or higher (API documentation: <https://docs.syncrosim.com/>).

An implementation of simulated maximum likelihood method for the estimation of Binary (Probit and Logit), Ordered (Probit and Logit) and Poisson models with random parameters for cross-sectional and longitudinal data as presented in Sarrias (2016) <doi:10.18637/jss.v074.i10>.

These tools were created to test map-scale hypotheses about trends in large remotely sensed data sets but any data with spatial and temporal variation can be analyzed. Tests are conducted using the PARTS method for analyzing spatially autocorrelated time series (Ives et al., 2021: <doi:10.1016/j.rse.2021.112678>). The method's unique approach can handle extremely large data sets that other spatiotemporal models cannot, while still appropriately accounting for spatial and temporal autocorrelation. This is done by partitioning the data into smaller chunks, analyzing chunks separately and then combining the separate analyses into a single, correlated test of the map-scale hypotheses.

This package provides a single key function, Require that makes rerun-tolerant versions of install.packages and `require` for CRAN packages, packages no longer on CRAN (i.e., archived), specific versions of packages, and GitHub packages. This approach is developed to create reproducible workflows that are flexible and fast enough to use while in development stages, while able to build snapshots once a stable package collection is found. As with other functions in a reproducible workflow, this package emphasizes functions that return the same result whether it is the first or subsequent times running the function, with subsequent times being sufficiently fast that they can be run every time without undue waiting burden on the user or developer.

Facilitates querying data from the â Facebook Marketing API', particularly for social science research <https://developers.facebook.com/docs/marketing-apis/>. Data from the Facebook Marketing API has been used for a variety of social science applications, such as for poverty estimation (Marty and Duhaut (2024) <doi:10.1038/s41598-023-49564-6>), disease surveillance (Araujo et al. (2017) <doi:10.48550/arXiv.1705.04045>), and measuring migration (Alexander, Polimis, and Zagheni (2020) <doi:10.1007/s11113-020-09599-3>). The package facilitates querying the number of Facebook daily/monthly active users for multiple location types (e.g., from around a specific coordinate to an administrative region) and for a number of attribute types (e.g., interests, behaviors, education level, etc). The package supports making complex queries within one API call and making multiple API calls across different locations and/or parameters.

This package provides randomization tests and graphical diagnostics for assessing randomized assignment and covariate balance for a binary treatment variable. See Branson (2021) <arXiv:1804.08760> for details.

Includes data analysis and meta-analysis functions (e.g., to calculate effect sizes and 95% Confidence Intervals (CI) on Standardised Effect Sizes (d) for AB/BA cross-over repeated-measures experimental designs), data presentation functions (e.g., density curve overlaid on histogram),and the data sets analyzed in different research papers in software engineering (e.g., related to software defect prediction or multi- site experiment concerning the extent to which structured abstracts were clearer and more complete than conventional abstracts) to streamline reproducible research in software engineering.

Implementation of the relative placement algorithm widely used in the scoring of Lindy Hop and West Coast Swing dance contests.

This package provides string arithmetic, reassignment operators, logical operators that handle missing values, and extra logical operators such as floating point equality and all or nothing. The intent is to allow R users to write code that is easier to read, write, and maintain while providing a friendlier experience to new R users from other language backgrounds (such as Python') who are used to concepts such as x += 1 and foo + bar'. Includes operators for not in, easy floating point comparisons, === equivalent, and SQL-like like operations (), etc. We also added in some extra helper functions, such as OS checks, pasting in Oxford comma format, and functions to get the first, last, nth, or most common element of a vector or word in a string.

Three methods to calculate R2 for models with correlated errors, including Phylogenetic GLS, Phylogenetic Logistic Regression, Linear Mixed Models (LMMs), and Generalized Linear Mixed Models (GLMMs). See details in Ives 2018 <doi:10.1093/sysbio/syy060>.

R implementation of SIDES-based subgroup search algorithms (Lipkovich et al. (2017) <doi:10.1002/sim.7064>).