Changes in version 2.1.3 (2025-10-21)                  

  - Adjusting for RcppArmadillo updates, as per CRAN request

                 Changes in version 2.1.2 (2022-11-02)                  

  - Adjustments for CRAN request

                 Changes in version 2.1.1 (2021-06-30)                  

  - Fixing a bug in the sample pre-processing for the special case of no
    duplicates + split estimation
  - Other small bug fixes

                 Changes in version 2.1.0 (2020-06-17)                  

  - Making Linux friendly
  - Adding more checks of input arguments
  - Removing duplicates in kernel methods
  - Returning the estimated coefficients in zvcv
  - Changing some input arguments for zvcv:

  - log_weight --> log_weights
  - folds_choose --> folds
  - obs_estim --> est_inds and is used to specify the estimation/fitting
    only samples (with the remainder being used for evaluation of the
    integrand
  - REMOVED obs_estim_choose, the option to specify the samples for each
    cross-validation fold. I think this level of flexibility would
    rarely be required and it cause confusion when est_inds is
    specified.

                        Changes in version 1.1.0                        

  - Added control functionals, semi-exact control functionals and
    approximate semi-exact control functionals

                        Changes in version 0.1.3                        

  - Adding k-fold cross validation to select the polynomial order and
    doing some documentation improvements

                        Changes in version 0.1.2                        

  - Speeding up the higher order polynomial matrix getter using C++

                        Changes in version 0.1.1                        

  - Allows for any order polynomial (with fast implementations available
    for polynomial orders Q = 1-4 or dimension d = 1)
  - A cross validation method which chooses the polynomial order
    starting at 1 and going to infinity is now implemented (this new
    method could allow for super-root-N convergence)

                        Changes in version 0.1.0                        

  - Initial release
  - Includes 1st - 4th order zero variance control variates
  - Regularisation is based on lasso or more generally elastic net where
    lambda is chosen using cross-validation and the elastic net
    parameter is specified