Template Model Builder: A General Random Effect Tool Inspired by 'ADMB'

With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.

'Rapidxml' C++ Header Files

Provides XML parsing capability through the 'Rapidxml' 'C++' header-only library.

A 'C++20' API for R

A header-only 'C++20' API for manipulating R data structures from 'C++'. Provides 'C++20' concepts specific to R, custom scalar and vector classes with built-in NA handling, automatic object protection, 'SIMD' (single-instruction-multiple-data), parallelisation, and a streamlined system for registering 'C++' functions, including templates, to R. Full API reference and documentation are available at < https://nicchr.github.io/cppally/>.

Solve Erlang-C Model

Provides a set of functions to solve Erlang-C model. The Erlang C formula was invented by the Danish Mathematician A.K. Erlang and is used to calculate the number of advisors and the service level.

Multiple Precision Arithmetic

Multiple Precision Arithmetic (big integers and rationals, prime number tests, matrix computation), "arithmetic without limitations" using the C library GMP (GNU Multiple Precision Arithmetic).

'Rcpp' Meets 'C++' Arrays

Interoperability between 'Rcpp' and the 'C++11' array and tuple types. Linking to this package allows fixed-length 'std::array' objects to be converted to and from equivalent R vectors, and 'std::tuple' objects converted to lists, via the as() and wrap() functions. There is also experimental support for 'std::span' from 'C++20'.

Testing for Change in C-Statistic

Calculate the confidence interval and p value for change in C-statistic. The adjusted C-statistic is calculated by using formula as "Somers' Dxy rank correlation"/2+0.5. The confidence interval was calculated by using the bootstrap method. The p value was calculated by using the Z testing method. Please refer to the article of Peter Ganz et al. (2016) .

C++ Tools for Cleaning Strings

Provides function declarations and inline function definitions that facilitate cleaning strings in C++ code before passing them to R.

Interface to the 'C++' Library 'Pf'

Builds and runs 'c++' code for classes that encapsulate state space model, particle filtering algorithm pairs. Algorithms include the Bootstrap Filter from Gordon et al. (1993) , the generic SISR filter, the Auxiliary Particle Filter from Pitt et al (1999) , and a variety of Rao-Blackwellized particle filters inspired by Andrieu et al. (2002) . For more details on the 'c++' library 'pf', see Brown (2020) .

Matching Algorithms in R and C++

Computes matching algorithms quickly using Rcpp. Implements the Gale-Shapley Algorithm to compute the stable matching for two-sided markets, such as the stable marriage problem and the college-admissions problem. Implements Irving's Algorithm for the stable roommate problem. Implements the top trading cycle algorithm for the indivisible goods trading problem.