prepare release (#44)

* Release 0.4.0 (#31)

* bump version

* add weights argument (#29)

* remove unused variable (#26)

* fix edf computation for deg = 2

* bump version + update docs

* remove package cache on appveyor

* weighted bandwidth selection

* weighted fitting

* adjust R interface

* add unit tests

* a few more sanity checks

* update docs

* update docs

* fix devtools install link

* stabilize weighted quantiles

* ensure scale != 0 in case of too many ties

* remove stripping of debug symbols

* prepare release

* update docs

* bump version

* update NEWS

* update docs

* update NEWS and DESCRIPTION

* update API docs

* backwards compatibility with bad code in rvineocpulib *sigh*

* initialization order warning

* typo in API doc

* CRAN comments

* API docs one more time

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: kde1d
 Type: Package
 Title: Univariate Kernel Density Estimation
-Version: 0.4.0
+Version: 1.0.0
 Authors@R: c(
         person("Thomas", "Nagler",, "mail@tnagler.com", role = c("aut", "cre")),
         person("Thibault", "Vatter",, "thibault.vatter@gmail.com", role = c("aut"))
@@ -25,7 +25,7 @@ Imports:
     qrng,
     stats,
     utils
-RoxygenNote: 6.1.1
+RoxygenNote: 7.0.0
 Suggests: 
     testthat
 URL: https://github.com/tnagler/kde1d

NEWS.md

@@ -1,3 +1,28 @@
+# kde1d 1.0.0
+
+NEW FEATURES
+
+  * optimal plug-in bandwidth selection for all polynomial degrees (#38).
+
+  * avoid randomness through simplified, deterministic jittering, see 
+  `equi_jitter()` (#40).
+
+  * removed dependency `cctools`.
+
+  * headers in `inst/include` can be used as standalone C++ library with 
+    convenience wrappers for R (#41).
+
+  * (several times) faster `pkde1d()`, `qkde1d()`, and `rkde1d()` due to
+    a more clever algorithm for numerical integration (#42).
+
+  * faster `kde1d()` thanks to the Fast Fourier Transform (#43).
+
+BUG FIXES
+
+  * improvements to numerical stability, inter- and extrapolation (#32, #35, 
+  #37).
+
+
 # kde1d 0.4.0
 
 NEW FEATURE

R/kde1d-methods.R

@@ -32,15 +32,38 @@
 #' @export
 dkde1d <- function(x, obj) {
   x <- prep_eval_arg(x, obj)
-  dkde1d_cpp(as.numeric(x), obj)
+  if (length(obj$jitter_info$i_disc) == 1) {
+    # for backwards compatibility with rvinecopulib
+    # TODO: remove next version
+    if (!is.ordered(x))
+      x <- ordered(x, obj$jitter_info$levels$x)
+    fhat <- dkde1d_cpp(as.numeric(x) - 1, obj)
+    f_all <- dkde1d_cpp(seq_along(obj$jitter_info$levels$x) - 1, obj)
+    fhat <- fhat / sum(f_all)
+  } else {
+    fhat <- dkde1d_cpp(x, obj)
+  }
 }
 
 #' @param q vector of quantiles.
 #' @rdname dkde1d
 #' @export
 pkde1d <- function(q, obj) {
   q <- prep_eval_arg(q, obj)
-  pkde1d_cpp(q, obj)
+  if (length(obj$jitter_info$i_disc) == 1) {
+    # for backwards compatibility with rvinecopulib
+    # TODO: remove next version
+    if (!is.ordered(q))
+      q <- ordered(q, obj$jitter_info$levels$x)
+    x_all <- as.ordered(obj$jitter_info$levels$x)
+    p_all <- dkde1d(x_all, obj)
+    p_total <- sum(p_all)
+    p <- sapply(q, function(y) sum(p_all[x_all <= y] / p_total))
+    p <- pmin(pmax(p, 0), 1)
+  } else {
+    p <- pkde1d_cpp(q, obj)
+  }
+  p
 }
 
 #' @param p vector of probabilities.
@@ -51,7 +74,14 @@ qkde1d <- function(p, obj) {
   if (is.ordered(obj$x)) {
     ## for discrete variables, add factor levels
     q <- ordered(levels(obj$x)[q + 1], levels(obj$x))
+  } else if (length(obj$jitter_info$i_disc) == 1) {
+    # for backwards compatibility with rvinecopulib
+    # TODO: remove next version
+    x_all <- as.ordered(obj$jitter_info$levels$x)
+    pp <- pkde1d(x_all, obj)
+    q <- x_all[vapply(p, function(y) which(y <= pp)[1], integer(1))]
   }
+
   q
 }
 

R/kde1d.R

@@ -1,7 +1,7 @@
 #' Univariate local-polynomial likelihood kernel density estimation
 #'
-#' The estimator can handle for bounded, unbounded, and discrete support, see
-#' *Details*.
+#' The estimators can handle data with bounded, unbounded, and discrete support,
+#' see *Details*.
 #'
 #' @param x vector (or one-column matrix/data frame) of observations; can be
 #'   `numeric` or `ordered`.
@@ -29,6 +29,7 @@
 #'   Discrete variables are handled via jittering (see, Nagler, 2018a, 2018b).
 #'   A specific form of deterministic jittering is used, see [equi_jitter()].
 #'
+#'
 #' @seealso [`dkde1d()`], [`pkde1d()`], [`qkde1d()`], [`rkde1d()`],
 #'   [`plot.kde1d()`], [`lines.kde1d()`]
 #'

R/tools.R

@@ -71,6 +71,12 @@ prep_eval_arg <- function(x, obj) {
     return(x)
 
   stopifnot(is.ordered(x))
+  if (length(obj$jitter_info$i_disc) == 1) {
+    # for backwards compatibility with rvinecopulib
+    # TODO: remove next version
+    return(x)
+  }
+
   if (!all(levels(x) %in% levels(obj$x)))
     stop("'x' contains levels that weren't present when fitting.")
   levels(x) <- levels(obj$x)

README.md

@@ -11,7 +11,8 @@
 - implements a univariate kernel density estimator that can handle
 bounded and discrete data. 
 - provides classical kernel density as well as log-linear and log-quadratic methods. 
-- is highly efficient due to spline interpolation and a C++ backend.
+- is highly efficient due to the Fast Fourier Transform, spline interpolation,
+  and a C++ backend.
 
 For details, see the 
 [API documentation](https://tnagler.github.io/kde1d/).

cran-comments.md

@@ -1,16 +1,14 @@
-Update following a request by Prof. Ripley to remove unconditional stripping of debug symbols.
-
 ## Test environments
-* ubuntu 12.04 on travis-ci (release, devel, oldrel)
-* win-builder (devel)
+* ubuntu 14.04 on travis-ci (release, devel, oldrel)
+* win-builder (devel, release)
 
 ## R CMD check results
 
 0 errors | 0 warnings | 0 notes
 
 ## revdepcheck results
 
-We checked 2 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
+Checked 2 reverse dependencies (Note is unrelated to this package):
 
- * We saw 0 new problems
- * We failed to check 0 packages
+rvinecopulib 0.3.2.1.1    0 errors | 0 warnings | 1 note                                
+vinereg 0.5.0             0 errors | 0 warnings | 0 notes