Ratio-of-Uniforms Simulation with Transformation
Initial estimates for Generalized Pareto parameters
Create external pointer to a C++ function for log_j
Create external pointer to a C++ function for phi_to_theta
Create external pointer to a C++ function for logf
Selecting the Box-Cox parameter in the 1D case using Rcpp
Selecting the Box-Cox parameter in the 1D case
Selecting the Box-Cox parameter for general d using Rcpp
Selecting the Box-Cox parameter for general d
Generalized Pareto posterior log-density
Generalized Pareto summary statistics
Plot diagnostics for an ru object
Print method for an "ru" object
Generalized Pareto simulation
Generalized ratio-of-uniforms sampling using C++ via Rcpp
Generalized ratio-of-uniforms sampling
Internal rust functions
rust: Ratio-of-Uniforms Simulation with Transformation
Summarizing ratio-of-uniforms samples
Uses the generalized ratio-of-uniforms (RU) method to simulate from univariate and (low-dimensional) multivariate continuous distributions. The user specifies the log-density, up to an additive constant. The RU algorithm is applied after relocation of mode of the density to zero, and the user can choose a tuning parameter r. For details see Wakefield, Gelfand and Smith (1991) <DOI:10.1007/BF01889987>, Efficient generation of random variates via the ratio-of-uniforms method, Statistics and Computing (1991) 1, 129-133. A Box-Cox variable transformation can be used to make the input density suitable for the RU method and to improve efficiency. In the multivariate case rotation of axes can also be used to improve efficiency. From version 1.2.0 the 'Rcpp' package <https://cran.r-project.org/package=Rcpp> can be used to improve efficiency.
Useful links