Client for accessing data journalism APIs from ProPublica <http://www.propublica.org/>.

Make optimal decisions for your personal or household finances. Use tools and methods that are selected carefully to align with academic consensus, bridging the gap between theoretical knowledge and practical application. They help you find your own personalized optimal discretionary spending or optimal asset allocation, and prepare you for retirement or financial independence. The optimal solution to this problems is extremely complex, and we only have a single lifetime to get it right. Fortunately, we now have the user-friendly tools implemented, that integrate life-cycle models with single-period net-worth mean-variance optimization models. Those tools can be used by anyone who wants to see what highly-personalized optimal decisions can look like. For more details see: Idzorek T., Kaplan P. (2024, ISBN:9781952927379), Haghani V., White J. (2023, ISBN:9781119747918).

Tu & Zhou (1999) <doi:10.1002/(SICI)1097-0258(19991030)18:20%3C2749::AID-SIM195%3E3.0.CO;2-C> showed that comparing the means of populations whose data-generating distributions are non-negative with excess zero observations is a problem of great importance in the analysis of medical cost data. In the same study, Tu & Zhou discuss that it can be difficult to control type-I error rates of general-purpose statistical tests for comparing the means of these particular data sets. This package allows users to perform a modified bootstrap-based t-test that aims to better control type-I error rates in these situations.

This package provides C++ header files to deal with color conversion from some color spaces to hexadecimal with Rcpp', and exports some color mapping functions for usage in R. Also exports functions to convert colors from the HSLuv color space for usage in R. HSLuv is a human-friendly alternative to HSL.

This package performs robust and sparse correlation matrix estimation. Robustness is achieved based on a simple robust pairwise correlation estimator, while sparsity is obtained based on thresholding. The optimal thresholding is tuned via cross-validation. See Serra, Coretto, Fratello and Tagliaferri (2018) <doi:10.1093/bioinformatics/btx642>.

This package performs RNA emulation and active learning proposed by Heo and Sung (2025) <doi:10.1080/00401706.2024.2376173> for multi-fidelity computer experiments. The RNA emulator is particularly useful when the simulations with different fidelity level are nonlinearly correlated. The hyperparameters in the model are estimated by maximum likelihood estimation.

The header-only modern C++ template library Magic Enum for static reflection of enums (to string, from string, iteration) is provided by this package. More information about the underlying library can be found at its repository at <https://github.com/Neargye/magic_enum>.

Offers bathymetric interpolation using Inverse Distance Weighted and Ordinary Kriging via the gstat and terra packages. Other functions focus on quantifying physical aquatic habitats (e.g., littoral, epliminion, metalimnion, hypolimnion) from interpolated digital elevation models (DEMs). Functions were designed to calculate these metrics across water levels for use in reservoirs but can be applied to any DEM and will provide values for fixed conditions. Parameters like Secchi disk depth or estimated photic zone, thermocline depth, and water level fluctuation depth are included in most functions.

The complete data set of open repair data, full compliant with the Open Repair Data Standards (ORDS). It combines the datasets contributed by partner organizations of the Open Repair Alliance (ORA). Last updated: 2021-02-22. The package also contains via quests enriched datasets on batteries, printer, mobiles, and tablets.

Calculate common survey data quality indicators for multi-item scales and matrix questions. Currently supports the calculation of response style indicators and response distribution indicators. For an overview on response quality indicators see Bhaktha N, Henning S, Clemens L (2024). Characterizing response quality in surveys with multi-item scales: A unified framework <https://osf.io/9gs67/>.

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

The R commander plug-in for robust principal component analysis. The Graphical User Interface for Principal Component Analysis (PCA) with Hubert Algorithm method.

This package provides API to Melbourne pedestrian and weather data <https://data.melbourne.vic.gov.au> in tidy data form.

We provide functions to perform an empirical small telescopes analysis. This package contains 2 functions, SmallTelescopes() and EstimatePower(). Users only need to call SmallTelescopes() to conduct the analysis. For more information on small telescopes analysis see Uri Simonsohn (2015) <doi:10.1177/0956797614567341>.

Kiefer-Wolfowitz maximum likelihood estimation for mixture models and some other density estimation and regression methods based on convex optimization. See Koenker and Gu (2017) REBayes: An R Package for Empirical Bayes Mixture Methods, Journal of Statistical Software, 82, 1--26, <DOI:10.18637/jss.v082.i08>.

This package provides a list of functions for the statistical analysis and the post-processing of the Markov Chains simulated by ChronoModel (see <http://www.chronomodel.fr> for more information). ChronoModel is a friendly software to construct a chronological model in a Bayesian framework. Its output is a sampled Markov chain from the posterior distribution of dates component the chronology. The functions can also be applied to the analyse of mcmc output generated by Oxcal software.

This package provides a set of tools for creation, manipulation, and modeling of tensors with arbitrary number of modes. A tensor in the context of data analysis is a multidimensional array. rTensor does this by providing a S4 class Tensor that wraps around the base array class. rTensor provides common tensor operations as methods, including matrix unfolding, summing/averaging across modes, calculating the Frobenius norm, and taking the inner product between two tensors. Familiar array operations are overloaded, such as index subsetting via [ and element-wise operations. rTensor also implements various tensor decomposition, including CP, GLRAM, MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some auxiliary functions include the Khatri-Rao product, Kronecker product, and the Hadamard product for a list of matrices.

The ability to plot raster graphics in PDF files can be useful when one needs multi-page documents, but the plots contain so many individual elements that (the usual) use of vector graphics results in inconveniently large file sizes. Internally, the package plots each individual page as a PNG, and then combines them in one PDF file.

Model based simulation of dynamic networks under tie-oriented (Butts, C., 2008, <doi:10.1111/j.1467-9531.2008.00203.x>) and actor-oriented (Stadtfeld, C., & Block, P., 2017, <doi:10.15195/v4.a14>) relational event models. Supports simulation from a variety of relational event model extensions, including temporal variability in effects, heterogeneity through dyadic latent class relational event models (DLC-REM), random effects, blockmodels, and memory decay in relational event models (Lakdawala, R., 2024 <doi:10.48550/arXiv.2403.19329>). The development of this package was supported by a Vidi Grant (452-17-006) awarded by the Netherlands Organization for Scientific Research (NWO) Grant and an ERC Starting Grant (758791).

Function for adapting the shape of the random walk Metropolis proposal as specified by robust adaptive Metropolis algorithm by Vihola (2012) <doi:10.1007/s11222-011-9269-5>. The package also includes fast functions for rank-one Cholesky update and downdate. These functions can be used directly from R or the corresponding C++ header files can be easily linked to other R packages.

The RcppClassic package provides a deprecated C++ library which facilitates the integration of R and C++. New projects should use the new Rcpp API in the Rcpp package.

Easily compute an aggregate ranking (also called a median ranking or a consensus ranking) according to the axiomatic approach presented by Cook et al. (2007). This approach minimises the number of violations between all candidate consensus rankings and all input (partial) rankings, and draws on a branch and bound algorithm and a heuristic algorithm to drastically improve speed. The package also provides an option to bootstrap a consensus ranking based on resampling input rankings (with replacement). Input rankings can be either incomplete (partial) or complete. Reference: Cook, W.D., Golany, B., Penn, M. and Raviv, T. (2007) <doi:10.1016/j.cor.2005.05.030>.

This package provides functions for the complete analysis of respiratory data. Consists of a set of functions that allow to preprocessing respiratory data, calculate both regular statistics and nonlinear statistics, conduct group comparison and visualize the results. Especially, Power Spectral Density ('PSD') (A. Eke (2000) <doi:10.1007/s004249900135>), MultiScale Entropy(MSE) ('Madalena Costa(2002) <doi:10.1103/PhysRevLett.89.068102>) and MultiFractal Detrended Fluctuation Analysis(MFDFA) ('Jan W.Kantelhardt (2002) <doi:10.1016/S0378-4371(02)01383-3>) were applied for the analysis of respiratory data.

Assessing the comparative performance of two logistic regression models or results of such models or classification models. Discrimination metrics include Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), and difference in Area Under the Curves (AUCs), Brier scores and Brier skill. Plots include Risk Assessment Plots, Decision curves and Calibration plots. Methods are described in Pickering and Endre (2012) <doi:10.1373/clinchem.2011.167965> and Pencina et al. (2008) <doi:10.1002/sim.2929>.