Changes in version 0.0.17 (2025-10-29)                 

  - Fixed failing equality tests for Macs (due to inferior accuracy)

                 Changes in version 0.0.16 (2025-10-27)                 

  - Defined EL0() as the univariate and EL1() as the multi-variate
    wrapper, subsumed by EL()
  - Added Extrapolated EL for applications where the convex hull can be
    violated
  - Re-implemented adjusted (2 variants) and balanced EL
  - Added Bartlett factor computation
  - Improved brentZero() root search, added two new extensions rules:
    "left" and "right"
  - Improved the damped Newton search, added several stopping criteria
    to prevent stalling

                 Changes in version 0.0.15 (2025-08-18)                 

  - Rewrote most of the internal functions in Rcpp for higher speed
  - Moved weightedEL to EL0 and cemplik -- now that it is in C++ -- to
    EL
  - Added Euclidean likelihood, EuL()
  - smoothEmplik() accepts attach.attributes = TRUE as a synonym for
    "all"
  - Fixed 2 bugs in the Taylor expansion related to the spanning
    condition

                 Changes in version 0.0.14 (2025-07-22)                 

  - Fixed a bug in the Taylor expansion for the case of convex hull
    condition failures
  - Removed unfinished functions for optimisation and constrained
    optimisation
  - Implemented adaptive bandwidths at each point of the evaluation grid
    for better smoothing
  - Added a draft version of the vignette showcasing the use of adaptive
    kernels for smoothing
  - Implemented a Wald-like Taylor expansion to allow mu to be outside
    the convex hull in weightedEL()
  - Sped up the fourth-order triangular kernel

                       Changes in version 0.0.13                        

  - Implemented Taylor expansion to allow mu to be outside the convex
    hull in weightedEL(), as in Owen (2013)
  - Replaced uniroot() with a C++ version of Brent's zero search for
    speed
  - Improved handling of influential observations in LSCV

                       Changes in version 0.0.12                        

  - Fixed a bug in prepareKernel() where a valid y vector with
    attributes would not pass the check.
  - Implemented a more accurate check for lambda being close to the
    boundary based on the relative search interval length in
    weightedEL().
  - weightedEL() preserves the names of the input vector in wts.
  - Sped up ctracelr() by using the previous lambda value in the search
    (~4 times faster).
  - The output of mllog() now has column names because it was confusing
    without them.
  - The output of svdlm() is now a vector, not a 1-column matrix.
  - Replaced certain instances of sapply() with vapply() in smoothing
    functions.
  - Added unit tests for some functions.

                       Changes in version 0.0.11                        

  - Added EUPL licence.
  - Initialised tests for unit testing.
  - Fixed the bug in DCV when weights were not taken into account.
  - Removed simulation functions for the paper (to be provided
    separately).
  - Added examples for most functions.

                       Changes in version 0.0.10                        

  - Feature: support for weighted kernel density and regression
    observation.
  - Feature: support for sparse weight matrices via
    sparseKernelWeightsCPP() to save memory.
  - Feature: observation de-duplication to speed up the non-parametric
    functions.
  - Feature: low-level C++ parallelisation and chunking to limit maximum
    RAM use (via RcppParallel).
  - Feature: leave-one-out kernel smoothing support for custom output
    grids.
  - Reworked mixed kernel density and regression workflow making use of
    the block data structure.
  - Bug fix: now there are time savings in multi-core mixed estimation.
  - Bug fix: in DCV, duplicated observations were not merged (now the
    LOO is the true LOO: duplicates of the same observation are also
    left out).
  - Improved the initial value choice for cross-validation (using a
    log-scale grid around the rule-of-thumb value).
  - Sped up C++ kernel functions with RcppArmadillo (20--50% speed gains
    through better iterations, code structure, and condition checks).

                        Changes in version 0.0.9                        

  - Added a vignette on non-parametric methods.
  - Added 4th-order C++ versions of all kernels (for bias reduction) and
    their convolutions.
  - Auto-detect cross-validation type (density or least-squares) based
    on the input.
  - Changed the default behaviour of Silverman's rule of thumb: use a
    robust estimator of SD (IQR/1.34).
  - Prepared a stub for discontinuous densities.
  - Moving the gradient-related functions to a new package, pnd.

                        Changes in version 0.0.8                        

  - Rewrote the C++ smoothers using RcppArmadillo for speed-up,
    refactored the kernel-related code.
  - Feature: Support for the 2nd-order uniform, triangular,
    Epanechnikov, and quartic kernel.

                        Changes in version 0.0.7                        

  - Feature: added functions for parallelised numerical differentiation.
  - Rewrote multi-variate weighted empirical likelihood functions to
    allow for Taylor approximations of the empirical likelihood function
    of any order.

                        Changes in version 0.0.6                        

  - Feature: getSELWeights now renormalises the weights to unity after
    trimming (by default, can be overridden via renormalise = FALSE).

                        Changes in version 0.0.5                        

  - Initial release.