hermiter v2.2.0

Breaking changes

The interface of hermiter has been simplified. The update_batch method has been removed in favor of providing the ability to initialize the hermite_estimator with an initial batch of observations. Several internal methods are no longer exported in the interests of simplicity.
The default values of N have been optimized for different settings. For univariate, non-exponentially weighted estimators, the default is now N = 50. For univariate, exponentially weighted estimators, the default is now N = 20. For bivariate, non-exponentially weighted estimators, the default is now N = 30. Finally, For bivariate, exponentially weighted estimators, the default is now N = 20.

Parallel implementation of batch updating using RcppParallel provides significant performance improvements on multicore systems. Note that this can be disabled by using options(hermiter.parallel = FALSE).

A method has been added for estimating the Kendall rank correlation coefficient in the bivariate setting.
The univariate quantile estimation method has been significantly enhanced in accuracy using series acceleration techniques. Series acceleration is enabled by default.
The univariate pdf and cdf methods have been significantly enhanced in accuracy using series acceleration techniques. Series acceleration is enabled by default.
The new default method for the univariate quantile estimation method, ‘interpolate’ is much faster than the alternate method, ‘bisection’ with nearly the same accuracy.
Added print and summary methods for both the univariate and bivariate hermite_estimator objects.
Convenience function added to calculate sums of Hermite functions.

The vignette hermiter, namely vignette("hermiter") has been extended to included examples pertaining to estimation of the Kendall Tau nonparametric correlation coefficient in the bivariate setting.

get_coefficients has been removed as it is redundant.
combine_hermite has been renamed to merge_hermite for clarity.
combine_pair has been renamed to merge_pair for clarity.
hermite_integral_val_quantile_adap has been renamed to hermite_integral_val_upper for clarity.

Bivariate Hermite estimators have been added with methods for estimating bivariate probability density functions and cumulative distribution functions along with Spearman’s rank correlation coefficients.
The bivariate estimators include methods to batch update or sequentially update.
Methods are also provided to consistently merge bivariate hermite_estimators.
Convenience methods have been added for calculating normalized Hermite functions, along with upper, lower and full domain integrals of the normalized Hermite functions.

The vignette hermiter, namely vignette("hermiter") has been extended to included examples pertaining to the bivariate Hermite series based estimators.

The method for merging univariate Hermite series based estimators has been improved, yielding greater accuracy when the hermite_estimators are standardized.
The method for estimating quantiles with the univariate Hermite series based estimator has been improved and is now consistent with the estimator in the literature.
Vectorized the univariate quantile estimation method.
Added further error trapping and other minor enhancements (also for C++ routines).