Retrieves efficiently and reliably Investors Exchange ('IEX') stock and market data using IEX Cloud API'. The platform is offered by Investors Exchange Group (IEX Group). Main goal is to leverage R capabilities including existing packages to effectively provide financial and statistical analysis as well as visualization in support of fact-based decisions. In addition, continuously improve and enhance Riex by applying best practices and being in tune with users feedback and requirements. Please, make sure to review and acknowledge Investors Exchange Group (IEX Group) terms and conditions before using Riex (<https://iexcloud.io/terms/>).

Rank-based (R) estimation and inference for linear models. Estimation is for general scores and a library of commonly used score functions is included.

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

The Function performs a parallel analysis using simulated polychoric correlation matrices. The nth-percentile of the eigenvalues distribution obtained from both the randomly generated and the real data polychoric correlation matrices is returned. A plot comparing the two types of eigenvalues (real and simulated) will help determine the number of real eigenvalues that outperform random data. The function is based on the idea that if real data are non-normal and the polychoric correlation matrix is needed to perform a Factor Analysis, then the Parallel Analysis method used to choose a non-random number of factors should also be based on randomly generated polychoric correlation matrices and not on Pearson correlation matrices. Random data sets are simulated assuming or a uniform or a multinomial distribution or via the bootstrap method of resampling (i.e., random permutations of cases). Also Multigroup Parallel analysis is made available for random (uniform and multinomial distribution and with or without difficulty factor) and bootstrap methods. An option to choose between default or full output is also available as well as a parameter to print Fit Statistics (Chi-squared, TLI, RMSEA, RMR and BIC) for the factor solutions indicated by the Parallel Analysis. Also weighted correlation matrices may be considered for PA.

Connect, query, and operate on information available from the Open Source Vulnerability database <https://osv.dev/>. Although CRAN has vulnerabilities listed, these are few compared to projects such as PyPI'. With tighter integration between R and Python', having an R specific package to access details about vulnerabilities from various sources is a worthwhile enterprise.

This web client interfaces Unpaywall <https://unpaywall.org/products/api>, formerly oaDOI, a service finding free full-texts of academic papers by linking DOIs with open access journals and repositories. It provides unified access to various data sources for open access full-text links including Crossref and the Directory of Open Access Journals (DOAJ). API usage is free and no registration is required.

Rasch model and extensions for survey data, using Conditional Maximum likelihood (CML). Carlo Cafiero, Sara Viviani, Mark Nord (2018) <doi:10.1016/j.measurement.2017.10.065>.

An R interface to estimate structured additive regression (STAR) models with BayesX'.

Really Poor Man's Graphical User Interface, used to create interactive R analysis sessions with simple R commands.

This package provides subsets with reference semantics, i.e. subsets which automatically reflect changes in the original object, and which optionally update the original object when they are changed.

This package provides tools for qPCR data analysis using Delta Ct and Delta Delta Ct methods, including t-test, Wilcoxon-test, ANOVA models, and publication-ready visualizations. The package supports multiple target, and multiple reference genes, and uses a calculation framework adopted from Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and Pfaffl methods.

An implementation of a stochastic heuristic method for performing multidimensional function optimization. The method is inspired in the Cross-Entropy Method. It does not relies on derivatives, neither imposes particularly strong requirements into the function to be optimized. Additionally, it takes profit from multi-core processing to enable optimization of time-consuming functions.

Data sets, and functions for simulating and fitting nonlinear time series with minification and nonparametric models.

ARFIMA, in-mean, external regressors and various GARCH flavors, with methods for fit, forecast, simulation, inference and plotting.

Interface for multiple data sources, such as the `EDDS` API <https://evds2.tcmb.gov.tr/index.php?/evds/userDocs> of the Central Bank of the Republic of Türkiye and the `FRED` API <https://fred.stlouisfed.org/docs/api/fred/> of the Federal Reserve Bank. Both data providers require API keys for access, which users can easily obtain by creating accounts on their respective websites. The package provides caching ability with the selection of periods to increase the speed and efficiency of requests. It combines datasets requested from different sources, helping users when the data has common frequencies. While combining data frames whenever possible, it also keeps all requested data available as separate data frames to increase efficiency.

We implement full-ranked, rank-penalized, and adaptive nuclear norm penalized estimation methods using multivariate mixture models proposed by Kang, Chen, and Yao (2022+).

This package provides functions for connecting to and interfacing with an Arduino or similar device. Functionality includes uploading of sketches, setting and reading digital and analog pins, and rudimentary servo control. This project is not affiliated with the Arduino company, <https://www.arduino.cc/>.

Density discontinuity testing (a.k.a. manipulation testing) is commonly employed in regression discontinuity designs and other program evaluation settings to detect perfect self-selection (manipulation) around a cutoff where treatment/policy assignment changes. This package implements manipulation testing procedures using local polynomial density estimators: rddensity() constructs test statistics and p-values given a prespecified cutoff, rdbwdensity() performs data-driven bandwidth selection, and rdplotdensity() constructs density plots.

Vector Graphics devices for Microsoft PowerPoint and Microsoft Excel'. Functions extending package officer are provided to embed DrawingML graphics into Microsoft PowerPoint presentations and Microsoft Excel workbooks.

An Eigen'-based computationally efficient C++ implementation for fitting various kriging models to data. This research is supported by U.S. National Science Foundation grant DMS-2310637.

We introduce a robust matrix factor model that explicitly incorporates tail behavior and employs a mean-shift term to avoid efficiency losses through pre-centering of observed matrices. More details on the methods related to our paper are currently under submission. A full reference to the paper will be provided in future versions once the paper is published.

This package provides functions to simulate and analyze data for a regression model with an interval censored covariate, as described in Morrison et al. (2021) <doi:10.1111/biom.13472>.

When assigned "R for Data Science" (Wickham, Ã etinkaya-Rundel, and Grolemund (2023, ISBN: 1492097402)), students should read the book and type in all the associated R commands themselves. Sadly, that never happens. These tutorials allow students to demonstrate (and their instructors to be sure) that all work has been completed. See Kane (2023) <https://ppbds.github.io/tutorial.helpers/articles/instructions.html> from the tutorial.helpers package for a background discussion.

This package provides a collection of palettes designed to integrate with ggplot', reflecting the color schemes associated with ConesaLab'.