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This package implements the ST-DBSCAN (spatio-temporal density-based spatial clustering of applications with noise) clustering algorithm for detecting spatially and temporally dense regions in point data, with a fast C++ backend via Rcpp'. Birant and Kut (2007) <doi:10.1016/j.datak.2006.01.013>.
Computes multivariate normal (MVN) densities, and samples from MVN distributions, when the covariance or precision matrix is sparse.
Data sets utilized by the SGP package as exemplars for users to conduct their own student growth percentiles (SGP) analyses.
This package implements a suite of sensitivity analysis tools that extends the traditional omitted variable bias framework and makes it easier to understand the impact of omitted variables in regression models, as discussed in Cinelli, C. and Hazlett, C. (2020), "Making Sense of Sensitivity: Extending Omitted Variable Bias." Journal of the Royal Statistical Society, Series B (Statistical Methodology) <doi:10.1111/rssb.12348>.
This package implements Support Vector Machine Oblique Decision Trees (SVMODT). Recursively builds classification trees using linear Support Vector Machines (SVM) hyperplanes at each node instead of axis-parallel splits, creating oblique decision boundaries. Features include multiple feature selection methods, dynamic feature subset strategies, class weight support for imbalanced datasets, pruning and feature penalization.
Scripts and exercises that use card shuffling to teach confidence interval comparisons for different estimators.
An interactive framework for simulating blockchain protocols using a hybrid R-Shiny and Python architecture. The package provides tools to visualize peer-to-peer network maps, manage supply chain logistics on-chain, and execute cross-border settlements via smart contract logic. It leverages the reticulate package to perform standardized cryptographic operations, including SHA-256 hashing, Merkle Tree construction, and ECDSA (Elliptic Curve Digital Signature Algorithm) key generation. This tool is designed for pedagogical demonstration and rapid prototyping of distributed ledger requirements.
Structural handling of identity numbers used in the Swedish administration such as personal identity numbers ('personnummer') and organizational identity numbers ('organisationsnummer').
Calculates a modified Simplified Surface Energy Balance Index (SSEBI) and the Evaporative Fraction (EF) using geospatial raster data such as albedo and surface-air temperature difference (TSâ TA). The SSEBI is computed from albedo and TSâ TA to estimate surface moisture and evaporative dynamics, providing a robust assessment of surface dryness while accounting for atmospheric variations. Based on Roerink, Su, and Menenti (2000) <doi:10.1016/S1464-1909(99)00128-8>.
Fits, spatially predicts, and temporally forecasts space-time data using Gaussian Process (GP): (1) spatially varying coefficient process models and (2) spatio-temporal dynamic linear models. Bakar et al., (2016). Bakar et al., (2015).
Data processing and visualizations for rodent vocalizations exported from DeepSqueak'. These functions are compatible with the SqueakR Shiny Dashboard, which can be used to visualize experimental results and analyses.
Storm is a distributed real-time computation system. Similar to how Hadoop provides a set of general primitives for doing batch processing, Storm provides a set of general primitives for doing real-time computation. . Storm includes a "Multi-Language" (or "Multilang") Protocol to allow implementation of Bolts and Spouts in languages other than Java. This R extension provides implementations of utility functions to allow an application developer to focus on application-specific functionality rather than Storm/R communications plumbing.
Code for describing and manipulating scuba diving profiles (depth-time curves) and decompression models, for calculating the predictions of decompression models, for calculating maximum no-decompression time and decompression tables, and for performing mixed gas calculations.
This package provides a convenient interface to the staticrypt by Robin Moisson <https://github.com/robinmoisson/staticrypt>---'Node.js package for adding a password protection layer to static HTML pages. This package can be integrated into the post-render process of quarto documents to secure them with a password.
An htmlwidget of the human body that allows you to hide/show and assign colors to 79 different body parts. The human widget is an htmlwidget', so it works in Quarto documents, R Markdown documents, or any other HTML medium. It also functions as an input/output widget in a shiny app.
Efficiently estimates treatment effects in settings with randomized staggered rollouts, using tools proposed by Roth and Sant'Anna (2023) <doi:10.48550/arXiv.2102.01291>.
Interface to the SIDRA (Sistema IBGE de Recuperação Automática) web service provided by the Brazilian Institute of Geography and Statistics (IBGE). Data are retrieved through the official API <https://apisidra.ibge.gov.br/>.
Surveys to collect employment data so as to obtain data estimates on the number of employed people, the number of unemployed, and other employment indicators.
This package provides tools for constructing, auditing, and visualizing temporal social interaction networks from event-log data. Supports graph construction from raw user-to-user interaction logs, longitudinal tracking of network structure, community dynamics, user role trajectories, and concentration of engagement over time. Designed for computational social science, platform analytics, and digital community health monitoring. Includes four longitudinal audit indices: the Network Drift Index ('NDI'), Community Fragmentation Index ('CFI'), Visibility Concentration Index ('VCI'), and Role Mobility Index ('RMI'). NDI', CFI', VCI', and RMI are purpose-built composite scores for longitudinal platform auditing.
This package provides a shiny application with a user-friendly interface for interactive data analysis. It supports exploratory data analysis through descriptive statistics, data visualization, statistical tests (e.g., normality assessment), linear modeling, data import, transformation and reporting. For more details see Shapiro and Wilk (1965) <doi:10.2307/2333709>.
An English language syllable counter, plus readability score measure-er. For readability, we support Flesch Reading Ease and Flesch-Kincaid Grade Level ('Kincaid et al'. 1975) <https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1055&context=istlibrary>, Automated Readability Index ('Senter and Smith 1967) <https://apps.dtic.mil/sti/citations/AD0667273>, Simple Measure of Gobbledygook (McLaughlin 1969), and Coleman-Liau (Coleman and Liau 1975) <doi:10.1037/h0076540>. The package has been carefully optimized and should be very efficient, both in terms of run time performance and memory consumption. The main methods are vectorized by document, and scores for multiple documents are computed in parallel via OpenMP'.
This package provides R functions for calculating basic effect size indices for single-case designs, including several non-overlap measures and parametric effect size measures, and for estimating the gradual effects model developed by Swan and Pustejovsky (2018) <DOI:10.1080/00273171.2018.1466681>. Standard errors and confidence intervals (based on the assumption that the outcome measurements are mutually independent) are provided for the subset of effect sizes indices with known sampling distributions.
This package provides comprehensive methods for sample size determination for epidemiological studies, clinical trials, diagnostic accuracy studies, and diagnostic agreement studies. The package supports prevalence surveys, cluster prevalence studies, unmatched case-control studies, cohort studies, superiority, non-inferiority, and equivalence clinical trials, diagnostic sensitivity, diagnostic specificity, receiver operating characteristic (ROC) area under the curve (AUC), and diagnostic agreement studies. Functions include optional adjustments for finite population correction, design effect, unequal allocation, anticipated response rate, and dropout. Results are returned as standardized SampleSizeR objects with print, summary, plot, and data frame methods.
Corrects the spelling of a given word in English using a modification of Peter Norvig's spell correct algorithm (see <http://norvig.com/spell-correct.html>) which handles up to three edits. The algorithm tries to find the spelling with maximum probability of intended correction out of all possible candidate corrections from the original word.