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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: VineCopula
 Type: Package
 Title: Statistical Inference of Vine Copulas
-Version: 2.3.0
+Version: 2.4.0
 Description: Provides tools for the statistical analysis of vine copula models.
     The package includes tools for parameter estimation, model selection,
     simulation, goodness-of-fit tests, and visualization. Tools for estimation,

diff --git a/NEWS.md b/NEWS.md
@@ -1,11 +1,22 @@
-VineCopula (in progress)
+VineCopula 2.4.0 (September 30, 2020)
 ----------------------------------------------------------------
 
 NEW FEATURES
 
-  * `RVineSim` optionally accepts a list of `RVineMatrix` models that must 
-    share the same structure, but can differ in in family/parameters (#69, #70).
-    Thanks @notEvil.
+  * `RVineSim` optionally accepts a length-`N` list of `RVineMatrix` models that 
+    must share the same structure, but can differ in in family/parameters (#69, #70).
+    In that case, simulation is vectorized and each draw corresponds to a model 
+    specification from the list. Thanks @notEvil.
+
+BUG FIXES
+
+  * fixed bug when excluding models from the family set by specifying a negative 
+    family index.
+
+  * throw appropriate error when `treecrit` function is misspecified.
+
+  * fix gcc11 error caused by (redundant) `printError()` in C-code.
+
 
 
 VineCopula 2.3.0 (November 26, 2019)

diff --git a/R/BiCopDeriv.R b/R/BiCopDeriv.R
@@ -60,7 +60,7 @@
 #' [BiCop()]
 #' @references Schepsmeier, U. and J. Stoeber (2014). Derivatives and Fisher
 #' information of bivariate copulas. Statistical Papers, 55 (2), 525-542. \cr
-#' <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #' @examples
 #'
 #' ## simulate from a bivariate Student-t copula

diff --git a/R/BiCopDeriv2.R b/R/BiCopDeriv2.R
@@ -69,7 +69,7 @@
 #' [BiCopDeriv()], [BiCopHfuncDeriv()], [BiCop()]
 #' @references Schepsmeier, U. and J. Stoeber (2014). Derivatives and Fisher
 #' information of bivariate copulas. Statistical Papers, 55 (2), 525-542. \cr
-#' <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #' @examples
 #'
 #' ## simulate from a bivariate Student-t copula

diff --git a/R/BiCopGofTest.R b/R/BiCopGofTest.R
@@ -112,7 +112,7 @@
 #' Scandinavian Journal of Statistics, 33(2), 337-366.
 #' Luo J. (2011). Stepwise estimation of D-vines with arbitrary specified
 #' copula pairs and EDA tools. Diploma thesis, Technische Universitaet
-#' Muenchen.\cr <http://mediatum.ub.tum.de/?id=1079291>.
+#' Muenchen.\cr <https://mediatum.ub.tum.de/?id=1079291>.
 #'
 #' White, H. (1982) Maximum likelihood estimation of misspecified models,
 #' Econometrica, 50, 1-26.

diff --git a/R/BiCopHfuncDeriv.R b/R/BiCopHfuncDeriv.R
@@ -56,7 +56,7 @@
 #' [BiCopHfuncDeriv()], [BiCop()]
 #' @references Schepsmeier, U. and J. Stoeber (2014). Derivatives and Fisher
 #' information of bivariate copulas. Statistical Papers, 55 (2), 525-542. \cr
-#' <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #' @examples
 #'
 #' ## simulate from a bivariate Student-t copula

diff --git a/R/BiCopHfuncDeriv2.R b/R/BiCopHfuncDeriv2.R
@@ -65,7 +65,7 @@
 #' [BiCopHfuncDeriv()], [BiCop()]
 #' @references Schepsmeier, U. and J. Stoeber (2014). Derivatives and Fisher
 #' information of bivariate copulas. Statistical Papers, 55 (2), 525-542. \cr
-#' <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #' @examples
 #'
 #' ## simulate from a bivariate Student-t copula

diff --git a/R/BiCopLambda.R b/R/BiCopLambda.R
@@ -88,7 +88,7 @@
 #' Schepsmeier, U. (2010). Maximum likelihood estimation of C-vine pair-copula
 #' constructions based on bivariate copulas from different families. Diploma
 #' thesis, Technische Universitaet Muenchen.\cr
-#' <http://mediatum.ub.tum.de/?id=1079296>.
+#' <https://mediatum.ub.tum.de/?id=1079296>.
 #'
 #' @examples
 #' \dontshow{set.seed(123)}

diff --git a/R/BiCopSelect.R b/R/BiCopSelect.R
@@ -133,7 +133,7 @@
 #'
 #' Brechmann, E. C. (2010). Truncated and simplified regular vines and their
 #' applications. Diploma thesis, Technische Universitaet Muenchen.\cr
-#' <http://mediatum.ub.tum.de/?id=1079285>.
+#' <https://mediatum.ub.tum.de/?id=1079285>.
 #'
 #' Manner, H. (2007). Estimation and model selection of copulas with an
 #' application to exchange rates. METEOR research memorandum 07/056, Maastricht

diff --git a/R/BiCopVuongClarke.R b/R/BiCopVuongClarke.R
@@ -105,7 +105,7 @@
 #' @references Belgorodski, N. (2010) Selecting pair-copula families for
 #' regular vines with application to the multivariate analysis of European
 #' stock market indices Diploma thesis, Technische Universitaet Muenchen.
-#' <http://mediatum.ub.tum.de/?id=1079284>.
+#' <https://mediatum.ub.tum.de/?id=1079284>.
 #'
 #' Clarke, K. A. (2007). A Simple Distribution-Free Test for Nonnested Model
 #' Selection. Political Analysis, 15, 347-363.

diff --git a/R/RVineGofTest3.R b/R/RVineGofTest3.R
@@ -185,7 +185,7 @@
 #'
 #' @references Berg, D. and H. Bakken (2007) A copula goodness-of-fit approach
 #' based on the conditional probability integral transformation.
-#' <http://www.danielberg.no/publications/Btest.pdf>
+#' <https://www.danielberg.no/publications/Btest.pdf>
 #'
 #' Breymann, W., A. Dias and P. Embrechts (2003) Dependence structures for
 #' multivariate high-frequency data in finance. Quantitative Finance 3, 1-14
@@ -197,7 +197,7 @@
 #' appear in Econometric Reviews
 #'
 #' Schepsmeier, U. (2013) A goodness-of-fit test for regular vine copula
-#' models.  Preprint <http://arxiv.org/abs/1306.0818>
+#' models.  Preprint <https://arxiv.org/abs/1306.0818>
 #'
 #' Schepsmeier, U. (2015) Efficient information based goodness-of-fit tests for
 #' vine copula models with fixed margins. Journal of Multivariate Analysis 138,

diff --git a/R/RVineGrad.R b/R/RVineGrad.R
@@ -69,14 +69,14 @@
 #' Schepsmeier, U. and J. Stoeber (2014)
 #' Derivatives and Fisher information of bivariate copulas.
 #' Statistical Papers, 55(2), 525-542.
-#' online first: <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' online first: <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #'
 #' Web supplement: Derivatives and Fisher Information of bivariate copulas.
-#' <http://mediatum.ub.tum.de/node?id=1119201>
+#' <https://mediatum.ub.tum.de/node?id=1119201>
 #'
 #' Stoeber, J. and U. Schepsmeier (2013). Estimating standard errors in regular
 #' vine copula models. Computational Statistics, 28 (6), 2679-2707
-#' <http://link.springer.com/article/10.1007/s00180-013-0423-8#>.
+#' <https://link.springer.com/article/10.1007/s00180-013-0423-8#>.
 #'
 #' @examples
 #'

diff --git a/R/RVineHessian.R b/R/RVineHessian.R
@@ -54,14 +54,14 @@
 #' Schepsmeier, U. and J. Stoeber (2014)
 #' Derivatives and Fisher information of bivariate copulas.
 #' Statistical Papers, 55(2), 525-542.
-#' online first: <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' online first: <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #'
 #' Web supplement: Derivatives and Fisher Information of bivariate copulas.
-#' <http://mediatum.ub.tum.de/node?id=1119201>
+#' <https://mediatum.ub.tum.de/node?id=1119201>
 #'
 #' Stoeber, J. and U. Schepsmeier (2013). Estimating standard errors in regular
 #' vine copula models. Computational Statistics, 28 (6), 2679-2707
-#' <http://link.springer.com/article/10.1007/s00180-013-0423-8#>.
+#' <https://link.springer.com/article/10.1007/s00180-013-0423-8#>.
 #'
 #' @examples
 #'

diff --git a/R/RVineMLE.R b/R/RVineMLE.R
@@ -76,7 +76,7 @@
 #'
 #' Stoeber, J. and U. Schepsmeier (2013). Estimating standard errors in regular
 #' vine copula models. Computational Statistics, 1-29
-#' <http://link.springer.com/article/10.1007/s00180-013-0423-8#>.
+#' <https://link.springer.com/article/10.1007/s00180-013-0423-8#>.
 #'
 #' @examples
 #'

diff --git a/R/RVineStdError.R b/R/RVineStdError.R
@@ -38,14 +38,14 @@
 #' Schepsmeier, U. and J. Stoeber (2014)
 #' Derivatives and Fisher information of bivariate copulas.
 #' Statistical Papers, 55(2), 525-542.
-#' online first: <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' online first: <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #'
 #' Web supplement: Derivatives and Fisher Information of bivariate copulas.
-#' <http://mediatum.ub.tum.de/node?id=1119201>
+#' <https://mediatum.ub.tum.de/node?id=1119201>
 #'
 #' Stoeber, J. and U. Schepsmeier (2013). Estimating standard errors in regular
 #' vine copula models. Computational Statistics, 28 (6), 2679-2707
-#' <http://link.springer.com/article/10.1007/s00180-013-0423-8#>.
+#' <https://link.springer.com/article/10.1007/s00180-013-0423-8#>.
 #'
 #' @examples
 #'

diff --git a/R/TauMatrix.R b/R/TauMatrix.R
@@ -1,6 +1,6 @@
 ###########################################
 # Algorithm for weighted tau adapted from matlab code by
-# http://www.mathworks.com/matlabcentral/fileexchange/27361-weighted-kendall-rank-correlation-matrix/content/kendalltau.m
+# https://www.mathworks.com/matlabcentral/fileexchange/27361-weighted-kendall-rank-correlation-matrix/content/kendalltau.m
 ############################################
 
 #' Matrix of Empirical Kendall's Tau Values

diff --git a/R/VineCopula-package.R b/R/VineCopula-package.R
@@ -46,7 +46,7 @@
 #'
 #' Brechmann, E. C. and U. Schepsmeier (2013). Modeling Dependence with C- and
 #' D-Vine Copulas: The R Package CDVine. Journal of Statistical Software, 52
-#' (3), 1-27. <http://www.jstatsoft.org/v52/i03/>.
+#' (3), 1-27. <https://www.jstatsoft.org/v52/i03/>.
 #'
 #' Czado, C., U. Schepsmeier, and A. Min (2012). Maximum likelihood estimation
 #' of mixed C-vines with application to exchange rates. Statistical Modelling,
@@ -58,7 +58,7 @@
 #'
 #' Eschenburg, P. (2013). Properties of extreme-value copulas Diploma thesis,
 #' Technische Universitaet Muenchen
-#' <http://mediatum.ub.tum.de/node?id=1145695>
+#' <https://mediatum.ub.tum.de/node?id=1145695>
 #'
 #' Joe, H. (1996). Families of m-variate distributions with given margins and
 #' m(m-1)/2 bivariate dependence parameters. In L. Rueschendorf, B. Schweizer,
@@ -82,18 +82,18 @@
 #'
 #' Schepsmeier, U. and J. Stoeber (2014). Derivatives and Fisher information of
 #' bivariate copulas. Statistical Papers, 55 (2), 525-542. \cr
-#' <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+#' <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 #'
 #' Schepsmeier, U. (2013) A goodness-of-fit test for regular vine copula
-#' models.  Preprint <http://arxiv.org/abs/1306.0818>
+#' models.  Preprint <https://arxiv.org/abs/1306.0818>
 #'
 #' Schepsmeier, U. (2015) Efficient information based goodness-of-fit tests for
 #' vine copula models with fixed margins. Journal of Multivariate Analysis 138,
 #' 34-52.
 #'
 #' Stoeber, J. and U. Schepsmeier (2013). Estimating standard errors in regular
 #' vine copula models. Computational Statistics, 28 (6), 2679-2707 \cr
-#' <http://link.springer.com/article/10.1007/s00180-013-0423-8#>.
+#' <https://link.springer.com/article/10.1007/s00180-013-0423-8#>.
 #'
 #' White, H. (1982) Maximum likelihood estimation of misspecified models,
 #' Econometrica, 50, 1-26.

diff --git a/README.md b/README.md
@@ -2,12 +2,12 @@ VineCopula
 ==========
 
 [![R build status](https://github.com/tnagler/VineCopula/workflows/R-CMD-check/badge.svg)](https://github.com/tnagler/VineCopula)
-[![CRAN version](http://www.r-pkg.org/badges/version/VineCopula)](https://cran.r-project.org/package=VineCopula) 
-[![CRAN downloads](http://cranlogs.r-pkg.org/badges/VineCopula)](https://cran.r-project.org/package=VineCopula)
+[![CRAN version](https://www.r-pkg.org/badges/version/VineCopula)](https://cran.r-project.org/package=VineCopula) 
+[![CRAN downloads](https://cranlogs.r-pkg.org/badges/VineCopula)](https://cran.r-project.org/package=VineCopula)
 
 Vine copulas are a flexible class of dependence models consisting of bivariate 
 building blocks (see e.g., Aas et al., 2009). You can find a comprehensive 
-list of publications and other materials on [vine-copula.org](http://www.statistics.ma.tum.de/en/research/vine-copula-models/).
+list of publications and other materials on [vine-copula.org](https://www.statistics.ma.tum.de/en/research/vine-copula-models/).
 
 This package is primarily made for the statistical analysis of **vine copula
 models**. The package includes tools for parameter estimation, model selection,
@@ -251,13 +251,13 @@ Brechmann, E. C., C. Czado, and K. Aas (2012). Truncated regular vines in high d
 
 Brechmann, E. C. and C. Czado (2011). Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50. Statistics & Risk Modeling, 30 (4), 307-342.
 
-Brechmann, E. C. and U. Schepsmeier (2013). Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine. Journal of Statistical Software, 52 (3), 1-27. <http://www.jstatsoft.org/v52/i03/>.
+Brechmann, E. C. and U. Schepsmeier (2013). Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine. Journal of Statistical Software, 52 (3), 1-27. <https://www.jstatsoft.org/v52/i03/>.
 
 Czado, C., U. Schepsmeier, and A. Min (2012). Maximum likelihood estimation of mixed C-vines with application to exchange rates. Statistical Modelling, 12(3), 229-255.
 
 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.
 
-Eschenburg, P. (2013). Properties of extreme-value copulas Diploma thesis, Technische Universitaet Muenchen <http://mediatum.ub.tum.de/node?id=1145695>.
+Eschenburg, P. (2013). Properties of extreme-value copulas Diploma thesis, Technische Universitaet Muenchen <https://mediatum.ub.tum.de/node?id=1145695>.
 
 Hofert, M., I. Kojadinovic, M. Maechler, and J. Yan (2015). copula: Multivariate
 Dependence with Copulas. R package version 0.999-13 
@@ -278,12 +278,12 @@ Nelsen, R. (2006). An introduction to copulas. Springer
 Nagler, T. (2015). kdecopula: Kernel Smoothing for Bivariate Copula Densities. R package
 version 0.6.0. <https://cran.r-project.org/package=kdecopula>
 
-Schepsmeier, U. and J. Stoeber (2012). Derivatives and Fisher information of bivariate copulas. Statistical Papers, 55 (2), 525-542. <http://link.springer.com/article/10.1007/s00362-013-0498-x>.
+Schepsmeier, U. and J. Stoeber (2012). Derivatives and Fisher information of bivariate copulas. Statistical Papers, 55 (2), 525-542. <https://link.springer.com/article/10.1007/s00362-013-0498-x>.
 
-Schepsmeier, U. (2013) A goodness-of-fit test for regular vine copula models. Preprint. <http://arxiv.org/abs/1306.0818>.
+Schepsmeier, U. (2013) A goodness-of-fit test for regular vine copula models. Preprint. <https://arxiv.org/abs/1306.0818>.
 
 Schepsmeier, U. (2015) Efficient information based goodness-of-fit tests for vine copula models with fixed margins. Journal of Multivariate Analysis 138, 34-52.
 
-Stoeber, J. and U. Schepsmeier (2013). Estimating standard errors in regular vine copula models. Computational Statistics, 28 (6), 2679-2707 <http://link.springer.com/article/10.1007/s00180-013-0423-8>.
+Stoeber, J. and U. Schepsmeier (2013). Estimating standard errors in regular vine copula models. Computational Statistics, 28 (6), 2679-2707 <https://link.springer.com/article/10.1007/s00180-013-0423-8>.
 
 White, H. (1982) Maximum likelihood estimation of misspecified models, Econometrica, 50, 1-26.
diff --git a/cran-comments.md b/cran-comments.md
@@ -1,14 +1,18 @@
+Fixes gcc11 warning (https://cran.r-project.org/web/checks/check_results_VineCopula.html)
+by removing the problematic function entirely.
+
 ## Test environments
 * ubuntu 16.04 (release) 
 * Windows Server 2019 (release) 
+* CRAN win builder (devel)
 * macOS Catalina 10.15 (devel, release)
 
 ## R CMD check results
 There were no ERROR or WARNINGs. 
 
 ## revdepcheck results
 
-We checked 10 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
+We checked 11 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
 
  * We saw 0 new problems
  * We failed to check 0 packages