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A 'Neo4J' Driver
A Modern and Flexible 'Neo4J' Driver, allowing you to query data on a 'Neo4J' server and handle the results in R. It's modern in the sense it provides a driver that can be easily integrated in a data analysis workflow, especially by providing an API working smoothly with other data analysis and graph packages. It's flexible in the way it returns the results, by trying to stay as close as possible to the way 'Neo4J' returns data. That way, you have the control over the way you will compute the results. At the same time, the result is not too complex, so that the "heavy lifting" of data wrangling is not left to the user.
Easy Dockerfile Creation from R
Build a Dockerfile straight from your R session. 'dockerfiler' allows you to create step by step a Dockerfile, and provide convenient tools to wrap R code inside this Dockerfile.
Functions Related to ICES Advice
A collection of functions that facilitate computational steps related to advice for fisheries management, according to ICES guidelines. These include methods for calculating reference points and model diagnostics.
Modelling Framework for the Estimation of Salmonid Abundance
A set of functions to estimate capture probabilities and densities from multipass pass removal data.
Import Professional Baseball Data from 'Retrosheet'
A collection of tools to import and structure the (currently) single-season event, game-log, roster, and schedule data available from < https://www.retrosheet.org>. In particular, the event (a.k.a. play-by-play) files can be especially difficult to parse. This package does the parsing on those files, returning the requested data in the most practical R structure to use for sabermetric or other analyses.
Interface to the 'sparseLM' Levenberg-Marquardt Library
Provides an R interface to the 'sparseLM' C library for
large-scale nonlinear least squares problems with arbitrarily sparse
Jacobians. The underlying solver implements a sparse variant of the
Levenberg-Marquardt algorithm for minimizing sum-of-squares objective
functions, supports user-supplied analytic Jacobians or finite-difference
approximation, and is designed to exploit sparsity for improved memory use
and performance. This package exposes the solver in R and uses sparse
matrix classes and the 'CHOLMOD' sparse Cholesky factorization routines
through the 'Matrix' package interface. Methods from the C library are
described in Lourakis (2010)
DATRAS Trawl Survey Database Web Services
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>.
String Distance Calculation with Tidy Data Principles
Calculation of string distance following the tidy data principles. Built on top of the 'stringdist' package.
Read and Process 'Pamguard' Binary Data
Functions for easily reading and processing binary data files created by 'Pamguard' (< https://www.pamguard.org/>). All functions for directly reading the binary data files are based on 'MATLAB' code written by Michael Oswald.
Gillespie's Stochastic Simulation Algorithm (SSA)
Provides a simple to use, intuitive, and
extensible interface to several stochastic simulation
algorithms for generating simulated trajectories of finite
population continuous-time model. Currently it implements
Gillespie's exact stochastic simulation algorithm (Direct
method) and several approximate methods (Explicit tau-leap,
Binomial tau-leap, and Optimized tau-leap). The package also
contains a library of template models that can be run as demo
models and can easily be customized and extended. Currently the
following models are included, 'Decaying-Dimerization' reaction
set, linear chain system, logistic growth model, 'Lotka'
predator-prey model, Rosenzweig-MacArthur predator-prey model,
'Kermack-McKendrick' SIR model, and a 'metapopulation' SIRS model.
Pineda-Krch et al. (2008)