Launches a shiny based application for Nuclear Magnetic Resonance (NMR)data importation and Statistical TOtal Correlation SpectroscopY (STOCSY) analyses in a full interactive approach. The theoretical background and applications of STOCSY method could be found at Cloarec, O., Dumas, M. E., Craig, A., Barton, R. H., Trygg, J., Hudson, J., Blancher, C., Gauguier, D., Lindon, J. C., Holmes, E. & Nicholson, J. (2005) <doi:10.1021/ac048630x>.

This package provides tools for assessment and quantification of individual identity information in animal signals. This package accompanies a research article by Linhart et al. (2019) <doi:10.1101/546143>: "Measuring individual identity information in animal signals: Overview and performance of available identity metrics".

This package implements the Interpolate, Truncate, Project (ITP) root-finding algorithm developed by Oliveira and Takahashi (2021) <doi:10.1145/3423597>. The user provides the function, from the real numbers to the real numbers, and an interval with the property that the values of the function at its endpoints have different signs. If the function is continuous over this interval then the ITP method estimates the value at which the function is equal to zero. If the function is discontinuous then a point of discontinuity at which the function changes sign may be found. The function can be supplied using either an R function or an external pointer to a C++ function. Tuning parameters of the ITP algorithm can be set by the user. Default values are set based on arguments in Oliveira and Takahashi (2021).

This package contains a series of R functions for calculating various chance-corrected agreement coefficients (CAC) among 2 or more raters. Among the CAC coefficients covered are Cohen's kappa, Conger's kappa, Fleiss kappa, Brennan-Prediger coefficient, Gwet's AC1/AC2 coefficients, and Krippendorff's alpha. Multiple sets of weights are proposed for computing weighted analyses. Also included in this package is Bangdiwala's B coefficient.

Time series plain text conversion and data visualization. It allows to transform IDEAM (Instituto de Hidrologia, Meteorologia y Estudios Ambientales) daily series from plain text to CSV files or data frames in R. Additionally, it is possible to obtain exploratory graphs from times series. IDEAMâ s data is freely delivered under formal request through the official web page <http://www.ideam.gov.co/solicitud-de-informacion>.

This package provides a lightweight interface to the iNaturalist API (<https://www.inaturalist.org/pages/api+reference>) for downloading observation photos and exporting metadata to CSV. Supports filtering by taxon, place, user, and annotation. Note that downloaded photos retain their original licenses as set by iNaturalist observers; users are responsible for respecting these licenses.

This package provides a curated reference list of countries and territories with classifications for Small Island Developing States (SIDS), sub-national island jurisdictions (SNIJ), World Bank region and income group, and political association. Sub-sovereign cases such as Aruba, Curacao, Bonaire, Sint Maarten, the French overseas territories, and Aaland Islands are represented with disambiguating codes that standard country-code packages often collapse or omit. Provides predicate helpers and a tidy joiner intended to extend rather than replace countrycode'. Source data is maintained at <https://github.com/University-of-Aruba/island-research-reference-data> and licensed CC BY 4.0.

This package provides functions are provided to interpolate geo-referenced point data via Inverse Path Distance Weighting. Useful for coastal marine applications where barriers in the landscape preclude interpolation with Euclidean distances.

It provides a generic set of tools for initializing a synthetic population with each individual in specific disease states, and making transitions between those disease states according to the rates calculated on each timestep. The new version 1.0.0 has C++ code integration to make the functions run faster. It has also a higher level function to actually run the transitions for the number of timesteps that users specify. Additional functions will follow for changing attributes on demographic, health belief and movement.

Four datasets are provided here from the Intendo game Super Jetroid'. It is data from the 2015 year of operation and it comprises a revenue table ('all_revenue'), a daily users table ('users_daily'), a user summary table ('user_summary'), and a table with data on all user sessions ('all_sessions'). These core datasets come in different sizes, and, each of them has a variant that was intentionally made faulty (totally riddled with errors and inconsistencies). This suite of tables is useful for testing with packages that focus on data validation and data documentation.

This package contains two main functions: one for solving general isotone regression problems using the pool-adjacent-violators algorithm (PAVA); another one provides a framework for active set methods for isotone optimization problems with arbitrary order restrictions. Various types of loss functions are prespecified.

Assists in generating binary clustered data, estimates of Intracluster Correlation coefficient (ICC) for binary response in 16 different methods, and 5 different types of confidence intervals.

Spatial interpolation toolkit designed for environmental and geospatial applications. It includes a range of methods, from traditional techniques to advanced machine learning approaches, ensuring accurate and efficient estimation of values in unobserved locations.

This package provides utilities to retrieve and manage ICD-10 code descriptions from Excel files. Supports vectors, data frame columns, and association rule outputs (e.g., arules objects) that require mapping to ICD-10 descriptions. Designed to simplify processing of healthcare datasets.

This package provides functions to estimate the probability to receive the observed treatment, based on individual characteristics. The inverse of these probabilities can be used as weights when estimating causal effects from observational data via marginal structural models. Both point treatment situations and longitudinal studies can be analysed. The same functions can be used to correct for informative censoring.

An eclectic collection of short stories and poetry with topics on climate strange, connecting the geopolitical dots, the myth of us versus them, and the idiocy of war. Please refer to the COPYRIGHTS file and the text_citation.cff file for the reference copyright information and for the complete citations of the reference sources, respectively.

Non-parametric resampling-based inference tests for ExPosition.

This package provides a shiny application to assist in phytosanitary inspections. It generates a diagram of pallets in a lot, highlights the units to be sampled, and documents them based on the selected sampling method (simple random or systematic sampling).

This package provides a collection of tools for detecting influential cases in generalized mixed effects models. It analyses models that were estimated using lme4'. The basic rationale behind identifying influential data is that when single units are omitted from the data, models based on these data should not produce substantially different estimates. To standardize the assessment of how influential a (single group of) observation(s) is, several measures of influence are common practice, such as Cook's Distance. In addition, we provide a measure of percentage change of the fixed point estimates and a simple procedure to detect changing levels of significance.

This package provides a bunch of functions to deal with circular data under order restrictions.

Computes individual contributions to the overall Gini and Theil's T and Theil's L measures and their decompositions by groups such as race, gender, national origin, with the three functions of iGini(), iTheiT(), and iTheilL(). For details, see Tim F. Liao (2019) <doi:10.1177/0049124119875961>.

Implementation of some of the formulations for the thermodynamic and transport properties released by the International Association for the Properties of Water and Steam (IAPWS). More specifically, the releases R1-76(2014), R5-85(1994), R6-95(2018), R7-97(2012), R8-97, R9-97, R10-06(2009), R11-24, R12-08, R15-11, R16-17(2018), R17-20 and R18-21 at <https://iapws.org>.

Allows the construction selection indices based on estimated breeding values in animal and plant breeding and to calculate several analytic measures around to assess its impact on genetic and phenotypic progress. The methodology thereby allows to analyze genetic gain of traits in the breeding goal which are not part of the actual index and automatically computes several analytic measures. It further allows to retrospectively derive realized economic weights from observed genetic trends. The framework is described in Simianer, H., Heise, J., Rensing, S., Pook, T. Geibel, J. and Reimer, C. (2023) <doi:10.1186/s12711-023-00807-0>.

Visualize interactions between multiple experimental factors using interactive 3D surface plots powered by plotly'. Instead of examining combinatorial pairwise interaction plots, map factor combinations to response surfaces and use surface crossings as geometric indicators of interaction effects. Supports continuous, categorical, and mixed factor designs with automatic binning for continuous conditioning variables.