Obtain Bayesian posterior distributions of dominance hierarchy steepness (Neumann and Fischer (2023) <doi:10.1111/2041-210X.14021>). Steepness estimation is based on Bayesian implementations of either Elo-rating or David's scores.

Build experience life tables.

Estimates extinction risk from population time series under a drifted Wiener process using the w-z method for accurate confidence intervals.

Computes and plots a transformed empirical CDF (ecdf) as a diagnostic for heavy tailed data, specifically data with power law decay on the tails. Routines for annotating the plot, comparing data to a model, fitting a nonparametric model, and some multivariate extensions are given.

Instead of counting observations before and after a subset() call, the ExclusionTable() function reports the number before and after each subset() call together with the number of observations that have been excluded. This is especially useful in observational studies for keeping track how many observations have been excluded for each in-/ or exclusion criteria. You just need to provide ExclusionTable() with a dataset and a list of logical filter statements.

Extra strength glue for data-driven templates. String interpolation for Shiny apps or R Markdown and knitr'-powered Quarto documents, built on the glue and whisker packages.

Interactive labelling of scatter plots, volcano plots and Manhattan plots using a shiny and plotly interface. Users can hover over points to see where specific points are located and click points on/off to easily label them. Labels can be dragged around the plot to place them optimally. Plots can be exported directly to PDF for publication. For plots with large numbers of points, points can optionally be rasterized as a bitmap, while all other elements (axes, text, labels & lines) are preserved as vector objects. This can dramatically reduce file size for plots with millions of points such as Manhattan plots, and is ideal for publication.

Easily create interactive charts by leveraging the Echarts Javascript library which includes 36 chart types, themes, Shiny proxies and animations.

This package provides a data transformation method which takes into account the special property of scale non-invariance with a breakpoint at 1 of the Euclidean distance.

This package provides tools for general properties including price, quantity, elasticity, convexity, marginal revenue and manifold of various economics demand systems including Linear, Translog, CES, LES and CREMR.

The EUNIS habitat classification is a comprehensive pan-European system for habitat identification <https://www.eea.europa.eu/data-and-maps/data/eunis-habitat-classification-1>. This is an R data package providing the EUNIS classification system. The classification is hierarchical and covers all types of habitats from natural to artificial, from terrestrial to freshwater and marine. The habitat types are identified by specific codes, names and descriptions and come with schema crosswalks to other habitat typologies.

Build entity relationship diagrams (ERD) to specify the nature of the relationship between tables in a database.

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 comprehensive toolkit for Distributed Elliptical model is designated as "ELIC" (The LIC for Distributed Elliptical Model Analysis) analysis. It is predicated on the assumption that the error term adheres to a Elliptical distribution. The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02664763.2022.2053949>.

Computes various effect sizes of the difference, their variance, and confidence interval. This package treats Cohen's d, Hedges d, biased/unbiased c (an effect size between a mean and a constant) and e (an effect size between means without assuming the variance equality).

Import gaze data from edf files generated by the SR Research <https://www.sr-research.com/> EyeLink eye tracker. Gaze data, both recorded events and samples, is imported per trial. The package allows to extract events of interest, such as saccades, blinks, etc. as well as recorded variables and custom events (areas of interest, triggers) into separate tables. The package requires EDF API library that can be obtained at <https://www.sr-research.com/support/>.

Exploitation, processing and 2D-3D visualization of DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, in a patient-oriented perspective.

This package provides functions for eleven procedures for determining the number of factors, including functions for parallel analysis and the minimum average partial test. There are also functions for conducting principal components analysis, principal axis factor analysis, maximum likelihood factor analysis, image factor analysis, and extension factor analysis, all of which can take raw data or correlation matrices as input and with options for conducting the analyses using Pearson correlations, Kendall correlations, Spearman correlations, gamma correlations, or polychoric correlations. Varimax rotation, promax rotation, and Procrustes rotations can be performed. Additional functions focus on the factorability of a correlation matrix, the congruences between factors from different datasets, the assessment of local independence, the assessment of factor solution complexity, internal consistency, and for correcting Pearson correlation coefficients for attenuation due to unreliability. Auerswald & Moshagen (2019, ISSN:1939-1463); Field, Miles, & Field (2012, ISBN:978-1-4462-0045-2); Mulaik (2010, ISBN:978-1-4200-9981-2); O'Connor (2000, <doi:10.3758/bf03200807>); O'Connor (2001, ISSN:0146-6216).

Implementation of the scaling functions presented in "General statistical scaling laws for stability in ecological systems" by Clark et al in Ecology Letters <DOI:10.1111/ele.13760>. Includes functions for extrapolating variability, resistance, and resilience across spatial and ecological scales, as well as a basic simulation function for producing time series, and a regression routine for generating unbiased parameter estimates. See the main text of the paper for more details.

This package provides a fast, flexible tool for generating disease surveillance reports from data exported from EpiTrax', a central repository for epidemiological data used by public health officials. It provides functions to manipulate EpiTrax datasets, tailor reports to internal or public use, and export reports in CSV, Excel xlsx', or PDF formats.

The EconDataverse is a universe of open-source packages to work seamlessly with economic data. This package is designed to make it easy to install and load multiple EconDataverse packages in a single step. Learn more about the EconDataverse at <https://www.econdataverse.org>.

The 2-D spatial and temporal Epidemic Type Aftershock Sequence ('ETAS') Model is widely used to decluster earthquake data catalogs. Usually, the calculation of standard errors of the ETAS model parameter estimates is based on the Hessian matrix derived from the log-likelihood function of the fitted model. However, when an ETAS model is fitted to a local data set over a time period that is limited or short, the standard errors based on the Hessian matrix may be inaccurate. It follows that the asymptotic confidence intervals for parameters may not always be reliable. As an alternative, this package allows for the construction of bootstrap confidence intervals based on empirical quantiles for the parameters of the 2-D spatial and temporal ETAS model. This version improves on Version 0.1.0 of the package by enabling the study space window (renamed study region') to be polygonal rather than merely rectangular. A Japan earthquake data catalog is used in a second example to illustrate this new feature.

Produce maximum likelihood estimates of common accuracy statistics for multiple measurement methods when a gold standard is not available. An R implementation of the expectation maximization algorithms described in Zhou et al. (2011) <doi:10.1002/9780470906514> with additional functions for creating simulated data and visualizing results. Supports binary, ordinal, and continuous measurement methods.

This package provides wrap functions to export and import graphics and data frames in R to microsoft office. And This package also provide write out figures with lots of different formats. Since people may work on the platform without GUI support, the package also provide function to easily write out figures to lots of different type of formats. Now this package provide function to extract colors from all types of figures and pdf files.