Nonparametric estimation of a unimodal or U-shape covariate effect under additive hazards model.

This package implements Minimum Torsion for portfolio diversification as described in Meucci, Attilio (2013) <doi:10.2139/ssrn.2276632>.

This package provides a container for data used by the usmap package. The data used by usmap has been extracted into this package so that the file size of the usmap package can be reduced greatly. The data in this package will be updated roughly once per year as new map data files are provided by the US Census Bureau.

This package provides functions for the creation and manipulation of scenes and objects within the Unity 3D video game engine (<https://unity.com/>). Specific focuses include the creation and import of terrain data and GameObjects as well as scene management.

For each string in a set of strings, determine a unique tag that is a substring of fixed size k unique to that string, if it has one. If no such unique substring exists, the least frequent substring is used. If multiple unique substrings exist, the lexicographically smallest substring is used. This lexicographically smallest substring of size k is called the "UniqTag" of that string.

Calculates federal and state income taxes in the United States. It acts as a wrapper to the NBER's TAXSIM 35 (<http://taxsim.nber.org/taxsim35/>) tax simulator. TAXSIM 35 conducts the calculations, while usincometaxes prepares the data for TAXSIM 35, sends the data to TAXSIM 35's server or communicates with the Web Assembly file, retrieves the data, and places it into a data frame. All without the user worrying about this process.

Univariate spline regression. It is possible to add the shape constraint of unimodality and predefined or self-defined penalties on the B-spline coefficients.

Format text (bold, italic, ...) and numbers using UTF-8. Offers functions to search for emojis and include them in your text.

Unit-Gompertz density, cumulative distribution, quantile functions and random deviate generation of the unit-Gompertz distribution. In addition, there are a function for fitting the Generalized Additive Models for Location, Scale and Shape.

Fit Bayesian hierarchical models of animal abundance and occurrence via the rstan package, the R interface to the Stan C++ library. Supported models include single-season occupancy, dynamic occupancy, and N-mixture abundance models. Covariates on model parameters are specified using a formula-based interface similar to package unmarked', while also allowing for estimation of random slope and intercept terms. References: Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.

This package provides researchers with a simple set of diagnostic tools for monitoring the progress and reliability of raters conducting content coding tasks. Goehring (2024) <https://bengoehring.github.io/improving-content-analysis-tools-for-working-with-undergraduate-research-assistants.pdf> argues that supervisors---especially supervisors of small teams---should utilize computational tools to monitor reliability in real time. As such, this package provides easy-to-use functions for calculating inter-rater reliability statistics and measuring the reliability of one coder compared to the rest of the team.

This package provides tools for formatting and summarizing data for outcomes research.

An R API providing easy access to a relational database with macroeconomic, financial and development related time series data for Uganda. Overall more than 5000 series at varying frequency (daily, monthly, quarterly, annual in fiscal or calendar years) can be accessed through the API. The data is provided by the Bank of Uganda, the Ugandan Ministry of Finance, Planning and Economic Development, the IMF and the World Bank. The database is being updated once a month.

This package provides functions and a Shiny application for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.

This package provides an extension to the Partial Credit Model and Generalized Partial Credit Models which allows for an additional person parameter that characterizes the uncertainty of the person. The method was originally proposed by Tutz and Schauberger (2020) <doi:10.1177/0146621620920932>.

Calculate several understandability metrics of BPMN models. BPMN stands for business process modelling notation and is a language for expressing business processes into business process diagrams. Examples of these understandability metrics are: average connector degree, maximum connector degree, sequentiality, cyclicity, diameter, depth, token split, control flow complexity, connector mismatch, connector heterogeneity, separability, structuredness and cross connectivity. See R documentation and paper on metric implementation included in this package for more information concerning the metrics.

Automatically converts language-specific verbal information, e.g., "1st half of the 19th century," to its standardized numerical counterparts, e.g., "1801-01-01/1850-12-31." It follows the recommendations of the MIDAS ('Marburger Informations-, Dokumentations- und Administrations-System'), see <doi:10.11588/artdok.00003770>.

Construct and plot objective hierarchies and associated value and utility functions. Evaluate the values and utilities and visualize the results as colored objective hierarchies or tables. Visualize uncertainty by plotting median and quantile intervals within the nodes of objective hierarchies. Get numerical results of the evaluations in standard R data types for further processing.

An alternative for downloading various United States Department of Agriculture (USDA) data from <https://quickstats.nass.usda.gov/> through R. You must sign up for an API token from the mentioned website in order for this package to work.

Connect to Uniprot <https://www.uniprot.org/> to retrieve information about proteins using their accession number such information could be name or taxonomy information, For detailed information kindly read the publication <doi:10.1016/j.jprot.2019.103613>.

This package implements mixtures of unrestricted skew-t factor analyzer models via the EM algorithm.

Changes the column names of the inputted dataset to the correct names from the Uniform Crime Report codebook for the "Offenses Known and Clearance by Arrest" datasets from 1998-2014.

This package implements functions to derive uncertainty intervals for (i) regression (linear and probit) parameters when outcome is missing not at random (non-ignorable missingness) introduced in Genbaeck, M., Stanghellini, E., de Luna, X. (2015) <doi:10.1007/s00362-014-0610-x> and Genbaeck, M., Ng, N., Stanghellini, E., de Luna, X. (2018) <doi:10.1007/s10433-017-0448-x>; and (ii) double robust and outcome regression estimators of average causal effects (on the treated) with possibly unobserved confounding introduced in Genbaeck, M., de Luna, X. (2018) <doi:10.1111/biom.13001>.

This package provides a simple interface to the Geographic Header information from the "2010 US Census Summary File 2". The entire Summary File 2 is described at <https://catalog.data.gov/dataset/census-2000-summary-file-2-sf2>, but note that this package only provides access to parts of the geographic header ('geoheader') of the file. In particular, only the first 101 columns of the geoheader are included and, more importantly, only rows with summary levels (SUMLEVs) 010 through 050 (nation down through county level) are included. In addition to access to (part of) the geoheader, the package also provides a decode function that takes a column name and value and, for certain columns, returns "the meaning" of that column (i.e., a "SUMLEV" value of 40 means "State"); without a value, the decode function attempts to describe the column itself.