Statistical distribution in OOP (Object Oriented Programming) way. This package proposes a R6 class interface to classic statistical distribution, and new distributions can be easily added with the class AbstractDist. A useful point is the generic fit() method for each class, which uses a maximum likelihood estimation to find the parameters of a dataset, see, e.g. Hastie, T. and al (2009) <isbn:978-0-387-84857-0>. Furthermore, the rv_histogram class gives a non-parametric fit, with the same accessors that for the classic distribution. Finally, three random generators useful to build synthetic data are given: a multivariate normal generator, an orthogonal matrix generator, and a symmetric positive definite matrix generator, see Mezzadri, F. (2007) <arXiv:math-ph/0609050>.

Access and handle APIs that use the international open311 GeoReport v2 standard for civic issue tracking <https://wiki.open311.org/GeoReport_v2/>. Retrieve civic service types and request data. Select and add available open311 endpoints and jurisdictions. Implicitly supports custom queries and open311 extensions. Requires a minimal number of hard dependencies while still allowing the integration in common R formats ('xml2', tibble', sf').

Generate random user data from the Random User Generator API. For more information, see <https://randomuser.me/>.

Implementations for several robust procedures that allow for (online) extraction of the signal of univariate or multivariate time series by applying robust regression techniques to a moving time window are provided. Included are univariate filtering procedures based on repeated-median regression as well as hybrid and trimmed filters derived from it; see Schettlinger et al. (2006) <doi:10.1515/BMT.2006.010>. The adaptive online repeated median by Schettlinger et al. (2010) <doi:10.1002/acs.1105> and the slope comparing adaptive repeated median by Borowski and Fried (2013) <doi:10.1007/s11222-013-9391-7> choose the width of the moving time window adaptively. Multivariate versions are also provided; see Borowski et al. (2009) <doi:10.1080/03610910802514972> for a multivariate online adaptive repeated median and Borowski (2012) <doi:10.17877/DE290R-14393> for a multivariate slope comparing adaptive repeated median. Furthermore, a repeated-median based filter with automatic outlier replacement and shift detection is provided; see Fried (2004) <doi:10.1080/10485250410001656444>.

Semi-Automated Marketing Mix Modeling (MMM) aiming to reduce human bias by means of ridge regression and evolutionary algorithms, enables actionable decision making providing a budget allocation and diminishing returns curves and allows ground-truth calibration to account for causation.

Extension to REddyProc that allows reading data from netCDF files.

The getconf command-line tool provided by libc allows querying of a large number of system variables. This package provides similar functionality.

Download large sections of GenBank <https://www.ncbi.nlm.nih.gov/genbank/> and generate a local SQL-based database. A user can then query this database using restez functions or through rentrez <https://CRAN.R-project.org/package=rentrez> wrappers.

This package provides tools for basic and advance cancer statistics and graphics. Groups individual data, merges registry data and population data, calculates age-specific rate, age-standardized rate, cumulative risk, estimated annual percentage rate with standards error. Creates graphics across variable and time, such as age-specific trends, bar chart and period-cohort trends.

The goal of rFIA is to increase the accessibility and use of the United States Forest Services (USFS) Forest Inventory and Analysis (FIA) Database by providing a user-friendly, open source toolkit to easily query and analyze FIA Data. Designed to accommodate a wide range of potential user objectives, rFIA simplifies the estimation of forest variables from the FIA Database and allows all R users (experts and newcomers alike) to unlock the flexibility inherent to the Enhanced FIA design. Specifically, rFIA improves accessibility to the spatial-temporal estimation capacity of the FIA Database by producing space-time indexed summaries of forest variables within user-defined population boundaries. Direct integration with other popular R packages (e.g., dplyr', tidyr', and sf') facilitates efficient space-time query and data summary, and supports common data representations and API design. The package implements design-based estimation procedures outlined by Bechtold & Patterson (2005) <doi:10.2737/SRS-GTR-80>, and has been validated against estimates and sampling errors produced by FIA EVALIDator'. Current development is focused on the implementation of spatially-enabled model-assisted and model-based estimators to improve population, change, and ratio estimates.

This package implements a high performance C++ parser for ActiGraph GT3X'/'GT3X+ data format (with extension .gt3x') for accelerometer samples. Activity samples can be easily read into a matrix or data.frame. This allows for storing the raw accelerometer samples in the original binary format to reserve space.

Description of the tables, both grouped and not grouped, with some associated data management actions, such as sorting the terms of the variables and deleting terms with zero numbers.

Issues RPC-JSON calls to bitcoind', the daemon of Bitcoin Cash (BCH), to extract transaction data from the blockchain. BCH is a fork of Bitcoin that permits a greater number of transactions per second. A BCH daemon is available under an MIT license from the Bitcoin Unlimited website <https://www.bitcoinunlimited.info>.

DBI/RJDBC interface to h2 database. h2 version 2.3.232 is included.

An implementation of functionalities to transform directed graphs that are bound to a set of known forbidden paths. There are several transformations, following the rules provided by Villeneuve and Desaulniers (2005) <doi: 10.1016/j.ejor.2004.01.032>, and Hsu et al. (2009) <doi: 10.1007/978-3-642-03095-6_60>. The resulting graph is generated in a data-frame format. See rsppfp website for more information, documentation an examples.

Read the data from Origin(R) project files ('*.opj') <https://www.originlab.com/doc/User-Guide/Origin-File-Types>. No write support is planned.

This package creates and maintains a build process for complex analytic tasks in R. Package allows to easily generate Makefile for the (GNU) make tool, which drives the build process by (in parallel) executing build commands in order to update results accordingly to given dependencies on changed data or updated source files.

This package provides a machine learning package for automatic text classification that makes it simple for novice users to get started with machine learning, while allowing experienced users to easily experiment with different settings and algorithm combinations. The package includes eight algorithms for ensemble classification (svm, slda, boosting, bagging, random forests, glmnet, decision trees, neural networks), comprehensive analytics, and thorough documentation.

Data sets are often corrupted by outliers. When data are multivariate outliers can be classified as case-wise or cell-wise. The latters are particularly challenge to handle. We implement a robust estimation procedure for Seemingly Unrelated Regression Models which is able to cope well with both type of outliers. Giovanni Saraceno, Fatemah Alqallaf, Claudio Agostinelli (2021) <doi:10.48550/arXiv.2107.00975>.

Build regular expressions piece by piece using human readable code. This package contains Unicode functionality, and is primarily intended to be used by package developers.

Analyzes and predicts from matrix population models (Caswell 2006) <doi:10.1002/9781118445112.stat07481>.

Univariate and multivariate versions of risk-based control charts. Univariate versions of control charts, such as the risk-based version of X-bar, Moving Average (MA), Exponentially Weighted Moving Average Control Charts (EWMA), and Cumulative Sum Control Charts (CUSUM) charts. The risk-based version of the multivariate T2 control chart. Plot and summary functions. Kosztyan et. al. (2016) <doi:10.1016/j.eswa.2016.06.019>.

Applies a given global-fit method to random partial tanglegrams of a fixed size to identify the associations, terminals, and nodes that maximize phylogenetic (in)congruence. It also includes functions to compute more easily the confidence intervals of classification metrics and plot results, reducing computational time. See Llaberia-Robledillo et al., (2023) <doi:10.1093/sysbio/syad016>.

This package provides a straightforward model to estimate soil migration rates across various soil contexts. Based on the compartmental, vertically-resolved, physically-based mass balance model of Soto and Navas (2004) <doi:10.1016/j.jaridenv.2004.02.003> and Soto and Navas (2008) <doi:10.1016/j.radmeas.2008.02.024>. RadEro provides a user-friendly interface in R, utilizing input data such as 137Cs inventories and parameters directly derived from soil samples (e.g., fine fraction density, effective volume) to accurately capture the 137Cs distribution within the soil profile. The model simulates annual 137Cs fallout, radioactive decay, and vertical diffusion, with the diffusion coefficient calculated from 137Cs reference inventory profiles. Additionally, it allows users to input custom parameters as calibration coefficients. The RadEro user manual and protocol, including detailed instructions on how to format input data and configuration files, can be found at the following link: <https://github.com/eead-csic-eesa/RadEro>.