Spatial analyses involving binning require that every bin have the same area, but this is impossible using a rectangular grid laid over the Earth or over any projection of the Earth. Discrete global grids use hexagons, triangles, and diamonds to overcome this issue, overlaying the Earth with equally-sized bins. This package provides utilities for working with discrete global grids, along with utilities to aid in plotting such data.

This package provides a simple approach to measure political sophistication based on open-ended survey responses. Discursive sophistication captures the complexity of individual attitude expression by quantifying its relative size, range, and constraint. For more information on the measurement approach see: Kraft, Patrick W. 2023. "Women Also Know Stuff: Challenging the Gender Gap in Political Sophistication." American Political Science Review (forthcoming).

Consider ambiguity in probabilistic descriptions by replacing a parametric probabilistic description of uncertainty by a non-parametric set of probability distributions in the form of a Density Ratio Class. This is of particular interest in Bayesian inference. The Density Ratio Class is particularly suited for this purpose as it is invariant under Bayesian inference, marginalization, and propagation through a deterministic model. Here, invariant means that the result of the operation applied to a Density Ratio Class is again a Density Ratio Class. In particular the invariance under Bayesian inference thus enables iterative learning within the same framework of Density Ratio Classes. The use of imprecise probabilities in general, and Density Ratio Classes in particular, lead to intervals of characteristics of probability distributions, such as cumulative distribution functions, quantiles, and means. The package is based on a sample of the distribution proportional to the upper bound of the class. Typically this will be a sample from the posterior in Bayesian inference. Based on such a sample, the package provides functions to calculate lower and upper class boundaries and lower and upper bounds of cumulative distribution functions, and quantiles. Rinderknecht, S.L., Albert, C., Borsuk, M.E., Schuwirth, N., Kuensch, H.R. and Reichert, P. (2014) "The effect of ambiguous prior knowledge on Bayesian model parameter inference and prediction." Environmental Modelling & Software. 62, 300-315, 2014. <doi:10.1016/j.envsoft.2014.08.020>. Sriwastava, A. and Reichert, P. "Robust Bayesian Estimation of Value Function Parameters using Imprecise Priors." Submitted. <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4973574>.

Item focussed recursive partitioning for simultaneous selection of items and variables that induce Differential Item Functioning (DIF) in dichotomous or polytomous items.

Work with data on Venetian doges and dogaresse and the noble families of the Republic of Venice, and use it for social network analysis, as used in Merelo (2022) <doi:10.48550/arXiv.2209.07334>.

Designed to support the visualization, numerical computation, qualitative analysis, model-data fusion, and stochastic simulation for autonomous systems of differential equations. Euler and Runge-Kutta methods are implemented, along with tools to visualize the two-dimensional phaseplane. Likelihood surfaces and a simple Markov Chain Monte Carlo parameter estimator can be used for model-data fusion of differential equations and empirical models. The Euler-Maruyama method is provided for simulation of stochastic differential equations. The package was originally written for internal use to support teaching by Zobitz, and refined to support the text "Exploring modeling with data and differential equations using R" by John Zobitz (2021) <https://jmzobitz.github.io/ModelingWithR/index.html>.

Create disposable R packages for testing. You can create, install and load multiple R packages with a single function call, and then unload, uninstall and destroy them with another function call. This is handy when testing how some R code or an R package behaves with respect to other packages.

Parse, format, and validate international phone numbers using Google's libphonenumber java library, <https://github.com/google/libphonenumber>.

Various methods for the identification of trend and seasonal components in time series (TS) are provided. Among them is a data-driven locally weighted regression approach with automatically selected bandwidth for equidistant short-memory time series. The approach is a combination / extension of the algorithms by Feng (2013) <doi:10.1080/02664763.2012.740626> and Feng, Y., Gries, T., and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598> and a brief description of this new method is provided in the package documentation. Furthermore, the package allows its users to apply the base model of the Berlin procedure, version 4.1, as described in Speth (2004) <https://www.destatis.de/DE/Methoden/Saisonbereinigung/BV41-methodenbericht-Heft3_2004.pdf?__blob=publicationFile>. Permission to include this procedure was kindly provided by the Federal Statistical Office of Germany.

Various kinds of designs for (industrial) experiments can be created. The package uses, and sometimes enhances, design generation routines from other packages. So far, response surface designs from package rsm', Latin hypercube samples from packages lhs and DiceDesign', and D-optimal designs from package AlgDesign have been implemented.

Utilities to represent, visualize, filter, analyse, and summarize time-depth recorder (TDR) data. Miscellaneous functions for handling location data are also provided.

Probability mass function, distribution function, quantile function, random generation and parameter estimation for the type I and III discrete Weibull distributions.

Automatic generation of finite state machine models of dynamic decision-making that both have strong predictive power and are interpretable in human terms. We use an efficient model representation and a genetic algorithm-based estimation process to generate simple deterministic approximations that explain most of the structure of complex stochastic processes. We have applied the software to empirical data, and demonstrated it's ability to recover known data-generating processes by simulating data with agent-based models and correctly deriving the underlying decision models for multiple agent models and degrees of stochasticity.

Intelligently assign samples to batches in order to reduce batch effects. Batch effects can have a significant impact on data analysis, especially when the assignment of samples to batches coincides with the contrast groups being studied. By defining a batch container and a scoring function that reflects the contrasts, this package allows users to assign samples in a way that minimizes the potential impact of batch effects on the comparison of interest. Among other functionality, we provide an implementation for OSAT score by Yan et al. (2012, <doi:10.1186/1471-2164-13-689>).

Statistical methods for DNA mixture analysis. This package is a lite-version of the DNAmixtures package to allow users without a HUGIN software license to experiment with the statistical methodology. While the lite-version aims to provide the full functionality it is noticeably less efficient than the original DNAmixtures package. For details on implementation and methodology see <https://dnamixtures.r-forge.r-project.org/>.

Given an initial set of points, this package minimizes the number of elements to discard from this set such that there exists at least one monotonic and convex mapping within pre-specified upper and lower bounds.

This package contains data sets, examples and software from the Second Edition of "Design of Observational Studies"; see Rosenbaum, P.R. (2010) <doi:10.1007/978-1-4419-1213-8>.

It is used to identify dysregulated pathways based on a pre-ranked gene pair list. A fast algorithm is used to make the computation really fast. The data in package DysPIAData is needed.

Estimates latent variables of public opinion cross-nationally and over time from sparse and incomparable survey data. DCPO uses a population-level graded response model with country-specific item bias terms. Sampling is conducted with Stan'. References: Solt (2020) <doi:10.31235/osf.io/d5n9p>.

We provide a list of functions for replicating the results of the Monte Carlo simulations and empirical application of Jiang et al. (2022). In particular, we provide corresponding functions for generating the three types of random data described in this paper, as well as all the estimation strategies. Detailed information about the data generation process and estimation strategy can be found in Jiang et al. (2022) <doi:10.48550/arXiv.2201.13004>.

This package provides a tool for manipulating data using the generic formula. A single formula allows to easily add, replace and remove variables before running the analysis.

Differential exon usage test for RNA-Seq data via an empirical Bayes shrinkage method for the dispersion parameter the utilizes inclusion-exclusion data to analyze the propensity to skip an exon across groups. The input data consists of two matrices where each row represents an exon and the columns represent the biological samples. The first matrix is the count of the number of reads expressing the exon for each sample. The second matrix is the count of the number of reads that either express the exon or explicitly skip the exon across the samples, a.k.a. the total count matrix. Dividing the two matrices yields proportions representing the propensity to express the exon versus skipping the exon for each sample.

Apply the Deductive Rational Method to a monthly series of flow or precipitation data to fill in missing data. The method is as described in: Campos, D.F., (1984, ISBN:9686194444).

This package provides read and write access to data and metadata from the DataONE network <https://www.dataone.org> of data repositories. Each DataONE repository implements a consistent repository application programming interface. Users call methods in R to access these remote repository functions, such as methods to query the metadata catalog, get access to metadata for particular data packages, and read the data objects from the data repository. Users can also insert and update data objects on repositories that support these methods.