The rerddapUtils package is an R package that is a set of four main functions designed to work with and extend the rerddap package. These functions includes one for restricting by season, one for splitting large requests, and two for working with projected datasets. There are also two utility functions that provide estimates of the size of a proposed rerddap::griddap() request.

Assesses the robustness of the community structure of a network found by one or more community detection algorithm to give indications about their reliability. It detects if the community structure found by a set of algorithms is statistically significant and compares the different selected detection algorithms on the same network. robin helps to choose among different community detection algorithms the one that better fits the network of interest. Reference in Policastro V., Righelli D., Carissimo A., Cutillo L., De Feis I. (2021) <https://journal.r-project.org/archive/2021/RJ-2021-040/index.html>.

This package provides a GUI for the orloca package is provided as a Rcmdr plug-in. The package deals with continuos planar location problems.

This package provides functions to retrieve data and metadata from providers that disseminate data by means of SDMX web services. SDMX (Statistical Data and Metadata eXchange) is a standard that has been developed with the aim of simplifying the exchange of statistical information. More about the SDMX standard and the SDMX Web Services can be found at: <https://sdmx.org>.

R6 class interface for handling relational database connections using DBI package as backend. The class allows handling of connections to e.g. PostgreSQL, MariaDB and SQLite. The purpose is having an intuitive object allowing straightforward handling of SQL databases.

Unified interface for creating LLM and Agent objects, generating responses and performing batch inference based on a type-checked and validated S7 backend. Features reasoning, structured output, memory management, and tool use. Supports Ollama <https://docs.ollama.com/api>, OpenAI'-compatible <https://developers.openai.com/api/reference/overview>, and Anthropic'-compatible <https://platform.claude.com/docs/en/api/getting-started> endpoints.

This package creates a header only package to link to the CGAL (Computational Geometry Algorithms Library) header files in Rcpp'. There are a variety of potential uses for the software such as Hilbert sorting, K-D Tree nearest neighbors, and convex hull algorithms. For more information about how to use the header files, see the CGAL documentation at <https://www.cgal.org>. Currently downloads version 6.2.1 of the CGAL header files.

This package contains tools for reading and writing data from or to files in the formats: akterm, dmna, Scintec Format-1, and Campbell Scientific TOA5.

Estimates and plots as a heat map the rolling window wavelet correlation (RWWC) coefficients statistically significant (within the 95% CI) between two regular (evenly spaced) time series. RolWinWavCor also plots at the same graphic the time series under study. The RolWinWavCor was designed for financial time series, but this software can be used with other kinds of data (e.g., climatic, ecological, geological, etc). The functions contained in RolWinWavCor are highly flexible since these contains some parameters to personalize the time series under analysis and the heat maps of the rolling window wavelet correlation coefficients. Moreover, we have also included a data set (named EU_stock_markets) that contains nine European stock market indices to exemplify the use of the functions contained in RolWinWavCor'. Methods derived from Polanco-Martà nez et al (2018) <doi:10.1016/j.physa.2017.08.065>).

This package provides a set of additional operators and helper functions to make R code easier to read, write, and maintain. Includes string arithmetic (such as foo + bar'), in-place reassignment operators (such as x += 1), logical operators that handle missing values, floating-point and strict ('JavaScript'-style) equality tests, between operators, and SQL'-style pattern matching. Also provides convenience helpers for type conversion, operating-system checks, complete-cases statistics, and string manipulation, such as Oxford-comma pasting and extracting the first, last, n-th, or most common element of a vector or word in a string. The goal is to give R users, particularly those coming from other languages such as Python', a friendlier and more consistent syntax.

Focused on linear, quadratic and cubic regression models, it has a function for calculating the models, obtaining a list with their parameters, and a function for making the graphs for the respective models.

This package implements efficient simulation procedures to estimate tail loss probabilities and conditional excess for a stock portfolio. The log-returns are assumed to follow a t-copula model with generalized hyperbolic or t marginals.

The Tabular Matrix Problems via Pseudoinverse Estimation (TMPinv) is a two-stage estimation method that reformulates structured table-based systems - such as allocation problems, transaction matrices, and input-output tables - as structured least-squares problems. Based on the Convex Least Squares Programming (CLSP) framework, TMPinv solves systems with row and column constraints, block structure, and optionally reduced dimensionality by (1) constructing a canonical constraint form and applying a pseudoinverse-based projection, followed by (2) a convex-programming refinement stage to improve fit, coherence, and regularization (e.g., via Lasso, Ridge, or Elastic Net).

Loads Axon Binary Files (both ABF and ABF2') created by Axon Instruments/Molecular Devices software such as pClamp'.

Finds a robust instrumental variables estimator using a high breakdown point S-estimator of multivariate location and scatter matrix.

This package provides a tool to exchange data between R and Raven sound analysis software (Cornell Lab of Ornithology). Functions work on data formats compatible with the R package warbleR'.

Does local optimization using two derivatives and trust regions. Guaranteed to converge to a local minimum of the objective function. This is a thread-safe C++ port of the algorithm in the trust package by Charles J. Geyer, exposed both as a drop-in R function and as a C-callable, thread-safe entry point (with function pointers registered for other packages to call without linking against this package's shared library) so it can be used from parallel C++ code such as in nlmixr2est'.

This package creates transition tables, summaries, and interactive Sankey diagrams from longitudinal person-term-state data. Sankey diagrams visualize flows between states with link widths proportional to flow counts; see Kennedy and Sankey (1898) "The Thermal Efficiency of Steam Engines" <doi:10.1680/imotp.1898.19100> and Schmidt (2008) "The Sankey Diagram in Energy and Material Flow Management: Part I: History" <doi:10.1111/j.1530-9290.2008.00004.x>. The minimum input schema is one row per person per term with an identifier, term, and categorical state.

Infer log-linear Poisson Graphical Model with an auxiliary data set. Hot-deck multiple imputation method is used to improve the reliability of the inference with an auxiliary dataset. Standard log-linear Poisson graphical model can also be used for the inference and the Stability Approach for Regularization Selection (StARS) is implemented to drive the selection of the regularization parameter. The method is fully described in <doi:10.1093/bioinformatics/btx819>.

Implementation of some functions to create quizzes in the GIFT format. This format is used by several Virtual Learning Environments such as Moodle.

It provides external jars required for the rjdverse (as rjd3toolkit', rjd3x13 and rjd3tramoseats').

An RStudio addin providing shortcuts for writing in Markdown'. This package provides a series of functions that allow the user to be more efficient when using Markdown'. For example, you can select a word, and put it in bold or in italics, or change the alignment of elements inside you Rmd. The idea is to map all the functionalities from remedy on keyboard shortcuts, so that it provides an interface close to what you can find in any other text editor.

This package provides a data mining approach for longitudinal and clustered data, which combines the structure of mixed effects model with tree-based estimation methods. See Sela, R.J. and Simonoff, J.S. (2012) RE-EM trees: a data mining approach for longitudinal and clustered data <doi:10.1007/s10994-011-5258-3>.

Selects one model with variable selection FDR controlled at a specified level. A q-value for each potential variable is also returned. The input, variable selection counts over many bootstraps for several levels of penalization, is modeled as coming from a beta-binomial mixture distribution.