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
ZVCV 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)
ZVCV 0.1.2
Speeding up the higher order polynomial matrix getter using C++
ZVCV 0.1.3
Adding k-fold cross validation to select the polynomial order and
doing some documentation improvements
ZVCV 1.1.0
Added control functionals, semi-exact control functionals and
approximate semi-exact control functionals
ZVCV 2.1.0
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.
ZVCV 2.1.1
Fixing a bug in the sample pre-processing for the special case of no
duplicates + split estimation
Other small bug fixes
ZVCV 2.1.2
Adjustments for CRAN request
ZVCV 2.1.3
Adjusting for RcppArmadillo updates, as per CRAN request