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Header-Only C++ Mathematical Optimization Library for 'Armadillo'
'Ensmallen' is a templated C++ mathematical optimization library (by the 'MLPACK' team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library and pairs the appropriate header files from 'armadillo' through the 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under similar terms. Note that 'Ensmallen' requires a compiler that supports 'C++14' and 'Armadillo' 10.8.2 or later.
Image Processing Library Based on 'CImg'
Fast image processing for images in up to 4 dimensions (two spatial dimensions, one time/depth dimension, one colour dimension). Provides most traditional image processing tools (filtering, morphology, transformations, etc.) as well as various functions for easily analysing image data using R. The package wraps 'CImg', < https://cimg.eu>, a simple, modern C++ library for image processing.
Testing, Monitoring, and Dating Structural Changes
Testing, monitoring and dating structural changes in (linear) regression models. strucchange features tests/methods from the generalized fluctuation test framework as well as from the F test (Chow test) framework. This includes methods to fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM, recursive/moving estimates) and F statistics, respectively. It is possible to monitor incoming data online using fluctuation processes. Finally, the breakpoints in regression models with structural changes can be estimated together with confidence intervals. Emphasis is always given to methods for visualizing the data.
Random Sampling Distribution C++ Routines for Armadillo
Provides popular sampling distributions C++ routines based in armadillo through a header file approach.
'C++' Headers for 'ggdmc' Package
A fast 'C++' implementation of the design-based, Diffusion Decision Model (DDM) and the Linear Ballistic Accumulation (LBA) model. It enables the user to optimise the choice response time model by connecting with the Differential Evolution Markov Chain Monte Carlo (DE-MCMC) sampler implemented in the 'ggdmc' package. The package fuses the hierarchical modelling, Bayesian inference, choice response time models and factorial designs, allowing users to build their own design-based models. For more information on the underlying models, see the works by Voss, Rothermund, and Voss (2004)
Rmetrics - Chronological and Calendar Objects
The 'timeDate' class fulfils the conventions of the ISO 8601 standard as well as of the ANSI C and POSIX standards. Beyond these standards it provides the "Financial Center" concept which allows to handle data records collected in different time zones and mix them up to have always the proper time stamps with respect to your personal financial center, or alternatively to the GMT reference time. It can thus also handle time stamps from historical data records from the same time zone, even if the financial centers changed day light saving times at different calendar dates.
Spatial Dependence: Weighting Schemes, Statistics
A collection of functions to create spatial weights matrix
objects from polygon 'contiguities', from point patterns by distance and
tessellations, for summarizing these objects, and for permitting their
use in spatial data analysis, including regional aggregation by minimum
spanning tree; a collection of tests for spatial 'autocorrelation',
including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord'
(1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel'
general cross product statistic, Empirical Bayes estimates and
'Assunção/Reis' (1999)
C-Statistics for Risk Prediction Models with Censored Survival Data
Performs inference for C of risk prediction models with censored survival data, using the method proposed by Uno et al. (2011)
Functions for Timing R Scripts, as Well as Implementations of "Stack" and "StackList" Structures
Code execution timing functions 'tic' and 'toc' that can be nested. One can record all timings while a complex script is running, and examine the values later. It is also possible to instrument the timing calls with custom callbacks. In addition, this package provides class 'Stack', implemented as a vector, and class 'StackList', which is a stack implemented as a list, both of which support operations 'push', 'pop', 'first_element', 'last_element' and 'clear'.
Fast Fixed-Effects Estimations
Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), instrumental variables (IV), generalized linear models (GLM), maximum likelihood estimation (ML), and the negative binomial.
The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Bergé, Butts, McDermott (2026)