Know which loop iteration the code execution is up to by including a single, convenient function call inside the loop.

Implementations of the weighted Kozachenko-Leonenko entropy estimator and independence tests based on this estimator, (Kozachenko and Leonenko (1987) <http://mi.mathnet.ru/eng/ppi797>). Also includes a goodness-of-fit test for a linear model which is an independence test between covariates and errors.

This package provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class incidence2 is used to store computed incidence and can be easily manipulated, subsetted, and plotted.

Pre-processing and basic analytical tasks for working with Eurostat's symmetric inputâ output tables, and basic inputâ output economics calculations. Part of rOpenGov <https://ropengov.github.io/> for open source open government initiatives.

Develops a General Equilibrium (GE) Model, which estimates key variables such as wages, the number of residents and workers, the prices of the floor space, and its distribution between commercial and residential use, as in Ahlfeldt et al., (2015) <doi:10.3982/ECTA10876>. By doing so, the model allows understanding the economic influence of different urban policies.

Mining informative genes with certain biological meanings are important for clinical diagnosis of disease and discovery of disease mechanisms in plants and animals. This process involves identification of relevant genes and removal of redundant genes as much as possible from a whole gene set. This package selects the informative genes related to a specific trait using gene expression dataset. These trait specific genes are considered as informative genes. This package returns the informative gene set from the high dimensional gene expression data using a combination of methods SVM and MRMR (for feature selection) with bootstrapping procedure.

The Importance Index (I.I.) can determine the loss and solution sources for a system in certain knowledge areas (e.g., agronomy), when production (e.g., fruits) is known (Demolin-Leite, 2021). Events (e.g., agricultural pest) can have different magnitudes (numerical measurements), frequencies, and distributions (aggregate, random, or regular) of event occurrence, and I.I. bases in this triplet (Demolin-Leite, 2021) <https://cjascience.com/index.php/CJAS/article/view/1009/1319>. Usually, the higher the magnitude and frequency of aggregated distribution, the greater the problem or the solution (e.g., natural enemies versus pests) for the system (Demolin-Leite, 2021). However, the final production of the system is not always known or is difficult to determine (e.g., degraded area recovery). A derivation of the I.I. is the percentage of Importance Index-Production Unknown (% I.I.-PU) that can detect the loss or solution sources, when production is unknown for the system (Demolin-Leite, 2024) <DOI:10.1590/1519-6984.253218>.

Calculate B-spline basis functions with a given set of knots and order, or a B-spline function with a given set of knots and order and set of de Boor points (coefficients), or the integral of a B-spline function.

Computes characteristics of independent rainfall events (duration, total rainfall depth, and intensity) extracted from a sub-daily rainfall time series based on the inter-event time definition (IETD) method. To have a reference value of IETD, it also analyzes/computes IETD values through three methods: autocorrelation analysis, the average annual number of events analysis, and coefficient of variation analysis. Ideal for analyzing the sensitivity of IETD to characteristics of independent rainfall events. Adams B, Papa F (2000) <ISBN: 978-0-471-33217-6>. Joo J et al. (2014) <doi:10.3390/w6010045>. Restrepo-Posada P, Eagleson P (1982) <doi:10.1016/0022-1694(82)90136-6>.

Let us consider a sample of patients who can suffer from several diseases simultaneously, in a given set of diseases. The goal of the implemented algorithm is to estimate the individual average cost of each disease, starting from the global health costs available for each patient.

Plot idiograms of karyotypes, plasmids, circular chr. having a set of data.frames for chromosome data and optionally mark data. Two styles of chromosomes can be used: without or with visible chromatids. Supports micrometers, cM and Mb or any unit. Three styles of centromeres are available: triangle, rounded and inProtein; and six styles of marks are available: square (squareLeft), dots, cM (cMLeft), cenStyle, upArrow (downArrow), exProtein (inProtein); its legend (label) can be drawn inline or to the right of karyotypes. Idiograms can also be plotted in concentric circles. It is possible to calculate chromosome indices by Levan et al. (1964) <doi:10.1111/j.1601-5223.1964.tb01953.x>, karyotype indices of Watanabe et al. (1999) <doi:10.1007/PL00013869> and Romero-Zarco (1986) <doi:10.2307/1221906> and classify chromosomes by morphology Guerra (1986) and Levan et al. (1964).

This package implements the item based collaborative filtering (IBCF) method for continues phenotypes in the context of plant breeding where data are collected for various traits that were studied in various environments proposed by Montesinos-López et al. (2017) <doi:10.1534/g3.117.300309>.

Interface to the OpenGWAS database API <https://api.opengwas.io/api/>. Includes a wrapper to make generic calls to the API, plus convenience functions for specific queries.

Fits covariate dependent partial correlation matrices for integrative models to identify differential networks between two groups. The methods are described in Class et. al., (2018) <doi:10.1093/bioinformatics/btx750> and Ha et. al., (2015) <doi:10.1093/bioinformatics/btv406>.

This package provides tools for parsing NOAA Integrated Surface Data ('ISD') files, described at <https://www.ncdc.noaa.gov/isd>. Data includes for example, wind speed and direction, temperature, cloud data, sea level pressure, and more. Includes data from approximately 35,000 stations worldwide, though best coverage is in North America/Europe/Australia. Data is stored as variable length ASCII character strings, with most fields optional. Included are tools for parsing entire files, or individual lines of data.

Carry out comparative authorship analysis of disputed and undisputed texts within the Likelihood Ratio Framework for expressing evidence in forensic science. This package contains implementations of well-known algorithms for comparative authorship analysis, such as Smith and Aldridge's (2011) Cosine Delta <doi:10.1080/09296174.2011.533591> or Koppel and Winter's (2014) Impostors Method <doi:10.1002/asi.22954>, as well as functions to measure their performance and to calibrate their outputs into Log-Likelihood Ratios.

Utility functions that implement and automate common sets of validation tasks. These functions are particularly useful to validate inputs, intermediate objects and output values in user-defined functions, resulting in tidier and less verbose functions.

This package provides tools to scrape, clean, and analyze football player data from Indonesian leagues and perform similarity-based scouting analysis using standardized numeric features. The similarity approach follows common vector-space methods as described in Manning et al. (2008, ISBN:9780521865715) and Salton et al. (1975, <doi:10.1145/361219.361220>).

R interface to access the web services of the ICES (International Council for the Exploration of the Sea) DATRAS trawl survey database <https://datras.ices.dk/WebServices/Webservices.aspx>.

This package provides functions to clean and process international trade data into an international trade network (ITN) are provided. It then provides a set a functions to undertake analysis and plots of the ITN (extract the backbone, centrality, blockmodels, clustering). Examining the key players in the ITN and regional trade patterns.

This package provides functions to measure and test imaginary cognitive social structure (CSS) motifs, which are patterns of perceived relationships among individuals in a social network. Includes tools for calculating motif frequencies, comparing observed motifs to expected distributions, and visualizing motif structures. Implements methods described in Tanaka and Vega Yon (2023) <doi:10.1016/j.socnet.2023.11.005>.

Facilitates the calculation of 40 different insulin sensitivity indices based on fasting, oral glucose tolerance test (OGTT), lipid (adipose), tracer (palmitate and glycerol rate), and DXA (fat mass) measurement values. Enables easy and accurate assessment of insulin sensitivity, critical for understanding and managing metabolic disorders like diabetes and obesity. Indices calculated are described in Gastaldelli (2022) <doi:10.1002/oby.23503>, Suleman (2024) <doi:10.1210/clinem/dgae275>, and Lorenzo (2010) <doi:10.1210/jc.2010-1144>.

Carries out instrumental variable estimation of causal effects, including power analysis, sensitivity analysis, and diagnostics. See Kang, Jiang, Zhao, and Small (2020) <http://pages.cs.wisc.edu/~hyunseung/> for details.

This package provides a lightweight R interface to the Interactive Brokers (IBKR) Client Portal REST API. Functions cover session management, account and portfolio queries, market data retrieval, and order placement and cancellation. Requires a locally running IBKR Client Portal Gateway.