Release 0.6.1.1.0 (#243)

* fix name of t copula in docs (fixes #237) (#239)

* force TLL to be nonnegative (#238)

* misc addition to docs (#241)

* mention igraph representation in docs/examples

* remove igraph link

* add to vinecop selection docs

* prepare release (#242)

* mention igraph representation in docs/examples

* remove igraph link

* add to vinecop selection docs

* bump version

* update NEWS

* update website

* latest sources

* fix faulty print patch

* bump version

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: rvinecopulib
 Type: Package
 Title: High Performance Algorithms for Vine Copula Modeling
-Version: 0.5.5.1.1
+Version: 0.6.1.1.0
 Authors@R: c(
         person("Thomas", "Nagler",, "[email protected]", role = c("aut", "cre")),
         person("Thibault", "Vatter",, "[email protected]", role = c("aut"))
@@ -13,7 +13,7 @@ Description: Provides an interface to 'vinecopulib', a C++ library for vine
  and more modern API, improved performances, especially in high dimensions, 
  nonparametric and multi-parameter families, and the ability to model discrete 
  variables. The 'rvinecopulib' package includes 'vinecopulib' as header-only 
- C++ library (currently version 0.5.5). Thus users do not need to install 
+ C++ library (currently version 0.6.1). Thus users do not need to install 
  'vinecopulib' itself in order to use 'rvinecopulib'. Since their initial 
  releases, 'vinecopulib' is licensed under the MIT License, and 'rvinecopulib' 
  is licensed under the GNU GPL version 3.

NEWS.md

@@ -1,3 +1,20 @@
+# rvinecopulib 0.6.1.1.0 (July 13, 2021)
+
+Release following the updates of vinecopulib to 0.6.1, see 
+https://github.com/vinecopulib/vinecopulib/releases. The most 
+relevant changes are summarized below.
+
+### BUG FIXES
+
+- improved documentation (#241, #239)
+
+- use `num_threads` in recursive calls to the inverse Rosenblatt
+
+- force TLL to be nonnegative (#238)
+
+- fix number of parameters for TLL
+
+
 # rvinecopulib 0.5.5.1.1 (December 15, 2020)
 
 Maintenance release following the changes to `all.equal()` in R 4.1.x.

R/bicop.R

@@ -64,7 +64,7 @@
 #' (`"gaussian"`, `"clayton"`, `"gumbel"`, `"frank"`, and `"joe"`),
 #'
 #' * `"twopar"` contains the parametric families with two parameters
-#' (`"student"`, `"bb1"`, `"bb6"`, `"bb7"`, and `"bb8"`),
+#' (`"t"`, `"bb1"`, `"bb6"`, `"bb7"`, and `"bb8"`),
 #'
 #' * `"elliptical"` contains the elliptical families,
 #'
@@ -73,7 +73,7 @@
 #' * `"BB"` contains the BB families,
 #'
 #' * `"itau"` families for which estimation by Kendall's tau inversion is
-#' available (`"indep"`,`"gaussian"`, `"student"`,`"clayton"`, `"gumbel"`,
+#' available (`"indep"`,`"gaussian"`, `"t"`,`"clayton"`, `"gumbel"`,
 #' `"frank"`, `"joe"`).
 #'
 #' @return

R/vinecop.R

@@ -1,7 +1,8 @@
 #' Fitting vine copula models
 #'
 #' Automated fitting and model selection for vine copula models with continuous
-#' or discrete data.
+#' or discrete data. Selection of the structure is performed using the algorithm
+#' of Dissmann et al. (2013).
 #'
 #' @inheritParams bicop
 #' @param family_set a character vector of families; see [bicop()] for
@@ -34,6 +35,9 @@
 #' @details
 #'
 #' ## Discrete variables
+#' The dependence measures used to select trees (default: Kendall's tau) are
+#' corrected for ties (see [wdm::wdm]).
+#'
 #' Let `n` be the number of observations and `d` the number of variables.
 #' When at least one variable is discrete, two types of
 #' "observations" are required in `data`: the first `n  x  d` block
@@ -68,7 +72,13 @@
 #'
 #' @seealso [vinecop()], [dvinecop()], [pvinecop()], [rvinecop()],
 #'   [plot.vinecop()], [contour.vinecop()]
+#' @references
+#' Dissmann, J. F., E. C. Brechmann, C. Czado, and D. Kurowicka (2013).
+#' *Selecting and estimating regular vine copulae and application to
+#' financial returns.* Computational Statistics & Data Analysis, 59 (1),
+#' 52-69.
 #' @export
+#'
 #' @examples
 #' ## simulate dummy data
 #' x <- rnorm(30) * matrix(1, 30, 5) + 0.5 * matrix(rnorm(30 * 5), 30, 5)

R/vinecop_plot.R

@@ -9,6 +9,9 @@
 #' If you want the contour boxes to be perfect squares, the plot height should
 #' be \code{1.25/length(tree)*(d - min(tree))} times the plot width.
 #'
+#' The `plot()` method returns an object that (among other things) contains the
+#' `igraph` representation of the graph; see *Examples*.
+#'
 #' @method plot vinecop_dist
 #'
 #' @aliases contour.vinecop_dist plot.vinecop contour.vinecop
@@ -39,15 +42,19 @@
 #'
 #' @examples
 #' # set up vine copula model
-#' d <- 20
-#' n <- 2e2
-#' u <- matrix(runif(n * d), n, d)
+#' u <- matrix(runif(20 * 10), 20, 10)
 #' vc <- vinecop(u, family = "indep")
 #'
 #' # plot
 #' plot(vc, tree = c(1, 2))
 #' plot(vc, edge_labels = "pair")
 #'
+#' # extract igraph representation
+#' plt <- plot(vc, edge_labels = "family_tau")
+#' igr_obj <- get("g", plt$plot_env)[[1]]
+#' igr_obj  # print object
+#' igraph::E(igr_obj)$name  # extract edge labels
+#'
 #' # set up another vine copula model
 #' pcs <- lapply(1:3, function(j) # pair-copulas in tree j
 #'   lapply(runif(4 - j), function(cor) bicop_dist("gaussian", 0, cor)))

README.md

@@ -158,7 +158,7 @@ Additionally, nonparametric families are also supported.
 | ------------- | --------------------- | ---------- |
 | -             | Independence          | "indep"    |
 | Elliptical    | Gaussian              | "gaussian" |
-| "             | Student t             | "student"  |
+| "             | Student t             | "t"        |
 | Archimedean   | Clayton               | "clayton"  |
 | "             | Gumbel                | "gumbel"   |
 | "             | Frank                 | "frank"    |
@@ -176,7 +176,7 @@ Note that several convenience vectors of families are included:
 * `"one_par"` contains the parametric families with a single parameter
 (`"gaussian"`, `"clayton"`, `"gumbel"`, `"frank"`, and `"joe"`)
 * `"two_par"` contains the parametric families with two parameters
-(`"student"`, `"bb1"`, `"bb6"`, `"bb7"`, and `"bb8"`)
+(`"t"`, `"bb1"`, `"bb6"`, `"bb7"`, and `"bb8"`)
 * `"elliptical"` contains the elliptical families
 * `"archimedean"` contains the archimedean families
 * `"BB"` contains the BB families
@@ -204,4 +204,5 @@ one or two parameters:
 References
 ----------
 
-Aas, K., C. Czado, A. Frigessi, and H. Bakken (2009). Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics 44 (2), 182-198.
+Aas, K., C. Czado, A. Frigessi, and H. Bakken (2009). Pair-copula constructions 
+of multiple dependence. Insurance: Mathematics and Economics 44 (2), 182-198.