Found 10000 packages in 0.02 seconds
Random Sampling Distribution C++ Routines for Armadillo
Provides popular sampling distributions C++ routines based in armadillo through a header file approach.
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.
'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)
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.
Structural Equation Modeling and Twin Modeling in R
Quickly create, run, and report structural equation models, and twin models.
See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS.
Timothy C. Bates, Michael C. Neale, Hermine H. Maes, (2019). umx: A library for Structural Equation and Twin Modelling in R.
Twin Research and Human Genetics, 22, 27-41.
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'.
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.
Functions for Nonlinear Least Squares Solutions - Updated 2022
Provides tools for working with nonlinear least squares problems. For the estimation of models reliable and robust tools than nls(), where the the Gauss-Newton method frequently stops with 'singular gradient' messages. This is accomplished by using, where possible, analytic derivatives to compute the matrix of derivatives and a stabilization of the solution of the estimation equations. Tools for approximate or externally supplied derivative matrices are included. Bounds and masks on parameters are handled properly.
Map Projections
Converts latitude/longitude into projected coordinates.
Diffs for R Objects
Generate a colorized diff of two R objects for an intuitive visualization of their differences.