This package provides a collection of synthetic datasets simulating sales transactions from a fictional company. The dataset includes various related tables that contain essential business and operational data, useful for analyzing sales performance and other business insights. Key tables included in the package are: - "sales": Contains data on individual sales transactions, including order details, pricing, quantities, and customer information. - "customer": Stores customer-specific details such as demographics, geographic location, occupation, and birthday. - "store": Provides information about stores, including location, size, status, and operational dates. - "orders": Contains details about customer orders, including order and delivery dates, store, and customer data. - "product": Contains data on products, including attributes such as product name, category, price, cost, and weight. - "calendar": A time-based table that includes date-related attributes like year, month, quarter, day, and working day indicators. This dataset is ideal for practicing data analysis, performing time-series analysis, creating reports, or simulating business intelligence scenarios.

This package provides a set of utilities for matching products in different classification codes used in international trade research. It supports concordance between the Harmonized System (HS0, HS1, HS2, HS3, HS4, HS5, HS combined), the Standard International Trade Classification (SITC1, SITC2, SITC3, SITC4), the North American Industry Classification System (NAICS combined), as well as the Broad Economic Categories (BEC), the International Standard of Industrial Classification (ISIC), and the Standard Industrial Classification (SIC). It also provides code nomenclature/descriptions look-up, Rauch classification look-up (via concordance to SITC2), and trade elasticity look-up (via concordance to HS0 or SITC3 codes).

Hardware-based support for CRC32C cyclic redundancy checksum function is made available for x86_64 systems with SSE2 support as well as for arm64', and detected at build-time via cmake with a software-based fallback. This functionality is exported at the C'-language level for use by other packages. CRC32C is described in RFC 3270 at <https://datatracker.ietf.org/doc/html/rfc3720> and is based on Castagnoli et al <doi:10.1109/26.231911>.

Convert text into synthesized speech and get a list of supported voices for a region. Microsoft's Cognitive Services Text to Speech REST API <https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/rest-text-to-speech?tabs=streaming> supports neural text to speech voices, which support specific languages and dialects that are identified by locale.

Data recorded as paths or trajectories may be suitably described by curves, which are independent of their parametrization. For the space of such curves, the package provides functionalities for reading curves, sampling points on curves, calculating distance between curves and for computing Tukey curve depth of a curve w.r.t. to a bundle of curves. For details see Lafaye De Micheaux, Mozharovskyi, and Vimond (2021) <doi:10.48550/arXiv.1901.00180>.

This package provides a set of functions to conduct Conjunctive Analysis of Case Configurations (CACC) as described in Miethe, Hart, and Regoeczi (2008) <doi:10.1007/s10940-008-9044-8>, and identify and quantify situational clustering in dominant case configurations as described in Hart (2019) <doi:10.1177/0011128719866123>. Initially conceived as an exploratory technique for multivariate analysis of categorical data, CACC has developed to include formal statistical tests that can be applied in a wide variety of contexts. This technique allows examining composite profiles of different units of analysis in an alternative way to variable-oriented methods.

Browser cookies are name-value pairs that are saved in a user's browser by a website. Cookies allow websites to persist information about the user and their use of the website. Here we provide tools for working with cookies in shiny apps, in part by wrapping the js-cookie JavaScript library <https://github.com/js-cookie/js-cookie>.

Package encapsulates standard expressions for distances, times, luminosities, and other quantities useful in observational cosmology, including molecular line observations. Currently coded for a flat universe only.

Joint distribution of number of crossings and the longest run in a series of independent Bernoulli trials. The computations uses an iterative procedure where computations are based on results from shorter series. The procedure conditions on the start value and partitions by further conditioning on the position of the first crossing (or none).

This package provides SPSS'- and SAS'-like output for cross tabulations of two categorical variables (CROSSTABS) and for hierarchical loglinear analyses of two or more categorical variables (LOGLINEAR). The methods are described in Agresti (2013, ISBN:978-0-470-46363-5), Ajzen & Walker (2021, ISBN:9780429330308), Field (2018, ISBN:9781526440273), Norusis (2012, ISBN:978-0-321-74843-0), Nussbaum (2015, ISBN:978-1-84872-603-1), Stevens (2009, ISBN:978-0-8058-5903-4), Tabachnik & Fidell (2019, ISBN:9780134790541), and von Eye & Mun (2013, ISBN:978-1-118-14640-8).

This package implements the general template for collaborative targeted maximum likelihood estimation. It also provides several commonly used C-TMLE instantiation, like the vanilla/scalable variable-selection C-TMLE (Ju et al. (2017) <doi:10.1177/0962280217729845>) and the glmnet-C-TMLE algorithm (Ju et al. (2017) <arXiv:1706.10029>).

Simple functions for plotting linear calibration functions and estimating standard errors for measurements according to the Handbook of Chemometrics and Qualimetrics: Part A by Massart et al. (1997) There are also functions estimating the limit of detection (LOD) and limit of quantification (LOQ). The functions work on model objects from - optionally weighted - linear regression (lm) or robust linear regression ('rlm from the MASS package).

This package provides functions for the input/output and visualization of medical imaging data in the form of CIFTI files <https://www.nitrc.org/projects/cifti/>.

This package provides easy and consistent time conversion for public health purposes. The time conversion functions provided here are between date, ISO week, ISO yearweek, ISO year, calendar month/year, season, season week.

Estimates hidden Markov models from the family of Cholesky-decomposed Gaussian hidden Markov models (CDGHMM) under various missingness schemes. This family improves upon estimation of traditional Gaussian HMMs by introducing parsimony, as well as, controlling for dropped out observations and non-random missingness. See Neal, Sochaniwsky and McNicholas (2024) <DOI:10.1007/s11222-024-10462-0>.

Create, query, and modify causal graphs. caugi (Causal Graph Interface) is a causality-first, high performance graph package that provides a simple interface to build, structure, and examine causal relationships.

This package provides functions to create contour-enhanced forest plots for meta-analysis, supporting binary outcomes (e.g., odds ratios, risk ratios), continuous outcomes (e.g., correlations), and prevalence estimates. Includes options for prediction intervals, customized colors, study labeling, and contour shading to highlight regions of statistical significance. Based on metafor and ggplot2'.

This package implements the Cross-contribution Compensating Multiple standard Normalization (CCMN) method described in Redestig et al. (2009) Analytical Chemistry <doi:10.1021/ac901143w> and other normalization algorithms.

Offers a diverse collection of datasets focused on cardiovascular and heart disease research, including heart failure, myocardial infarction, aortic dissection, transplant outcomes, cardiovascular risk factors, drug efficacy, and mortality trends. Designed for researchers, clinicians, epidemiologists, and data scientists, the package features clinical, epidemiological, and simulated datasets covering a wide range of conditions and treatments such as statins, anticoagulants, and beta blockers. It supports analyses related to disease progression, treatment effects, rehospitalization, and public health outcomes across various cardiovascular patient populations.

Defines the classes and functions used to simulate and to analyze data sets describing copy number variants and, optionally, sequencing mutations in order to detect clonal subsets. See Zucker et al. (2019) <doi:10.1093/bioinformatics/btz057>.

Calculate date of birth, age, and gender, and generate anonymous sequence numbers from CPR numbers. <https://en.wikipedia.org/wiki/Personal_identification_number_(Denmark)>.

Germline and somatic locus data which contain the total read depth and B allele read depth using Bayesian model (Dirichlet Process) to cluster. Meanwhile, the cluster model can deal with the SNVs mutation and the CNAs mutation.

Get programmatic access to the open data provided by the Czech Statistical Office (CZSO, <https://csu.gov.cz>).

This package provides function declarations and inline function definitions that facilitate communication between R and the Eigen C++ library for linear algebra and scientific computing.