feat: density, hcdf, quantile, cor, median and IQR functions added

.Rbuildignore

@@ -5,3 +5,4 @@
 ^cran-comments\.md$
 ^data-raw$
 ^CRAN-RELEASE$
+^CRAN-SUBMISSION$

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: hermiter
 Title: Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Nonparametric Correlation (Bivariate)
-Version: 2.2.0
-Date: 2022-11-12
+Version: 2.3.0
+Date: 2023-05-07
 Authors@R: c(
   person("Michael","Stephanou",role=c("aut","cre"), email="[email protected]"),
   person("Melvin","Varughese",role="ctb"))
@@ -17,7 +17,7 @@ Description: Facilitates estimation of full univariate and bivariate
   Based on: Stephanou, Michael, Varughese, Melvin and Macdonald, Iain. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245>, 
   Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z> and Stephanou, Michael and Varughese, Melvin. "Sequential estimation of Spearman rank correlation using Hermite series estimators." Journal of Multivariate Analysis (2021) <doi:10.1016/j.jmva.2021.104783>.
 License: MIT + file LICENSE
-Depends: R (>= 3.5.0)
+Depends: R (>= 3.6.0)
 Imports: 
   Rcpp (>= 1.0.5),
   methods,
@@ -27,7 +27,7 @@ LinkingTo:
   BH,
   RcppParallel
 SystemRequirements: GNU make
-RoxygenNote: 7.2.2
+RoxygenNote: 7.2.3
 Suggests: 
     testthat,
     magrittr,
@@ -38,7 +38,8 @@ Suggests:
     ggplot2,
     DT,
     mvtnorm,
-    patchwork
+    patchwork,
+    colorspace
 VignetteBuilder: knitr
 ByteCompile: true
 URL: https://github.com/MikeJaredS/hermiter

NAMESPACE

@@ -1,12 +1,23 @@
 useDynLib("hermiter", .registration=TRUE)
 importFrom(Rcpp, evalCpp)
 importFrom(RcppParallel, RcppParallelLibs)
+importFrom(stats,quantile)
+importFrom(stats,density)
+importFrom(stats,median)
+importFrom("grDevices", "hcl.colors")
+importFrom("graphics", "abline", "filled.contour", "plot.default")
 importFrom("methods", "is")
 S3method(merge_hermite,list)
 S3method(merge_pair,hermite_estimator_univar)
 S3method(cum_prob,hermite_estimator_univar)
+S3method(hcdf,hermite_estimator_univar)
 S3method(dens,hermite_estimator_univar)
+S3method(density,hermite_estimator_univar)
 S3method(quant,hermite_estimator_univar)
+S3method(quantile,hermite_estimator_univar)
+S3method(median,hermite_estimator_univar)
+S3method(IQR,hermite_estimator_univar)
+S3method(IQR,default)
 S3method(quant,hermite_estimator_bivar)
 S3method(calculate_running_std,hermite_estimator_univar)
 S3method(calculate_running_std,hermite_estimator_bivar)
@@ -16,26 +27,41 @@ S3method(kendall,hermite_estimator_bivar)
 S3method(spearmans,hermite_estimator_univar)
 S3method(kendall,hermite_estimator_univar)
 S3method(cum_prob,hermite_estimator_bivar)
+S3method(hcdf,hermite_estimator_bivar)
 S3method(dens,hermite_estimator_bivar)
+S3method(density,hermite_estimator_bivar)
 S3method(update_sequential,hermite_estimator_bivar)
 S3method(merge_pair,hermite_estimator_bivar)
 S3method(summary,hermite_estimator_univar)
 S3method(print,hermite_estimator_univar)
 S3method(summary,hermite_estimator_bivar)
 S3method(print,hermite_estimator_bivar)
+S3method(print,hcdf_univar)
+S3method(plot,hcdf_univar)
+S3method(summary,hcdf_univar)
+S3method(print,hcdf_bivar)
+S3method(plot,hcdf_bivar)
+S3method(summary,hcdf_bivar)
+S3method(print,hdensity_univar)
+S3method(plot,hdensity_univar)
+S3method(print,hdensity_bivar)
+S3method(plot,hdensity_bivar)
 export(hermite_estimator)
 export(update_sequential)
 export(merge_hermite)
 export(merge_pair)
 export(cum_prob)
+export(hcdf)
 export(dens)
 export(quant)
 export(spearmans)
 export(kendall)
+export(cor)
 export(hermite_normalization_N)
 export(hermite_function_N)
 export(hermite_function_sum_N)
 export(hermite_polynomial_N)
 export(hermite_int_lower)
 export(hermite_int_upper)
-export(hermite_int_full)
+export(hermite_int_full)
+export(IQR)

NEWS.md

@@ -1,3 +1,24 @@
+# hermiter v2.3.0
+
+## Additions and improvements
+
+* Enhanced the update_sequential method to incorporate a single or multiple
+new observations.
+* Added density generic function which outputs an object with associated print
+and plot generics.
+* Added quantile generic function for convenience.
+* Added hcdf function which outputs an object with associated print, 
+plot and summary generics.
+* Added median and IQR convenience functions.
+* Added a wrapper around the stats::cor function with two new methods, namely
+"hermite.spearman" and "hermite.kendall".
+
+## Minor improvements and bug fixes
+
+* Additional test cases have been added.
+* Updated the vignette.
+* Fixed the SystemRequirements: C++11 note.
+
 # hermiter v2.2.0
 
 ## Breaking changes

R/hermite_estimator.R

@@ -188,9 +188,11 @@ merge_hermite.list <- function(hermite_estimators){
 #'
 #' @param h_est_obj A hermite_estimator_univar or hermite_estimator_bivar 
 #' object.
-#' @param x A numeric value or vector. An observation to be incorporated into 
-#' the estimator. Note that for univariate estimators, x is a numeric value 
-#' whereas for bivariate estimators, x is a numeric vector of length 2.
+#' @param x A numeric vector or matrix. Observations to be incorporated into 
+#' the estimator. Note that for univariate estimators, x is a numeric vector 
+#' whereas for bivariate estimators, x is a numeric vector of length 2 or a 
+#' n x 2 matrix with n bivariate observations to be incorporated into the 
+#' estimator.
 #' @return An object of class hermite_estimator_univar or 
 #' hermite_estimator_bivar.
 #' @export
@@ -282,6 +284,30 @@ cum_prob <- function(h_est_obj, x, clipped, accelerate_series = TRUE) {
   UseMethod("cum_prob", h_est_obj)
 }
 
+#' Creates an object summarizing the CDF with associated generic methods print,
+#' plot and summary.
+#'
+#' The h_est_obj object must be updated with observations prior to the use of 
+#' the method.
+#'
+#' @param h_est_obj A hermite_estimator_univar or hermite_estimator_bivar 
+#' object.
+#' @param clipped A boolean value. This value determines whether
+#' cumulative probabilities are clipped to lie between 0 and 1.
+#' @param accelerate_series A boolean value. This value determines whether
+#' Hermite series acceleration is applied.
+#' @param x_lower A numeric value (univariate) or a numeric vector (bivariate).
+#' This value determines the lower limit of x values at which to evaluate 
+#' the CDF.
+#' @param x_upper A numeric value (univariate) or a numeric vector (bivariate).
+#' This value determines the upper limit of x values at which to evaluate 
+#' the CDF.
+#' @return A hcdf_univar or hcdf_bivar object.
+hcdf <- function(h_est_obj, clipped = FALSE, accelerate_series = TRUE, 
+                 x_lower = NA, x_upper = NA) {
+  UseMethod("hcdf", h_est_obj)
+}
+
 #' Estimates the quantiles at a vector of probability values
 #' 
 #' This method utilizes the estimator (13) in paper Stephanou, Michael,