Running 'termTests_rank.R' [4s]
Running the tests in 'tests/termTests_rank.R' failed.
Complete output:
  > #  File tests/termTests_rank.R in package ergm.rank, part of the Statnet suite
  > #  of packages for network analysis, https://statnet.org .
  > #
  > #  This software is distributed under the GPL-3 license.  It is free,
  > #  open source, and has the attribution requirements (GPL Section 7) at
  > #  https://statnet.org/attribution
  > #
  > #  Copyright 2008-2019 Statnet Commons
  > #######################################################################
  > library(ergm.rank)
  Loading required package: ergm
  Loading required package: network
  
  'network' 1.17.1 (2021-06-12), part of the Statnet Project
  * 'news(package="network")' for changes since last version
  * 'citation("network")' for citation information
  * 'https://statnet.org' for help, support, and other information
  
  
  'ergm' 4.0.0 (2021-06-14), part of the Statnet Project
  * 'news(package="ergm")' for changes since last version
  * 'citation("ergm")' for citation information
  * 'https://statnet.org' for help, support, and other information
  
  'ergm' 4 is a major release that introduces a fair number of
  backwards-incompatible changes. Please type 'news(package="ergm")' for
  a list of major changes.
  
  
  'ergm.rank' 1.2.0 (2019-05-15), part of the Statnet Project
  * 'news(package="ergm.rank")' for changes since last version
  * 'citation("ergm.rank")' for citation information
  * 'https://statnet.org' for help, support, and other information
  
  > 
  > local1.nonconformity <- function(m){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(k) sapply(1:n, function(l) if(length(unique(c(i,j,k,l)))==4) (m[i,l]>m[i,j])*(m[l,j]>m[l,k])*(1-(m[i,j]>m[i,k])) else 0 )))))
  + }
  > local2.nonconformity <- function(m){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(k) sapply(1:n, function(l) if(length(unique(c(i,j,k,l)))==4) (m[i,l]>m[i,k])*(m[l,j]>m[l,k])*(1-(m[i,j]>m[i,k])) else 0 )))))
  + }
  > localAND.nonconformity <- function(m){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(k) sapply(1:n, function(l) if(length(unique(c(i,j,k,l)))==4) (m[i,l]>m[i,k] && m[i,l]>m[i,j])*(m[l,j]>m[l,k])*(1-(m[i,j]>m[i,k])) else 0 )))))
  + }
  > global.nonconformity <- function(m){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(k) sapply(1:n, function(l) if(length(unique(c(i,j,k,l)))==4) (m[l,j]>m[l,k])*(1-(m[i,j]>m[i,k])) else 0 )))))
  + }
  > deference <- function(m){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(l) if(length(unique(c(i,j,l)))==3) (m[l,j]>m[l,i])*(m[i,l]>m[i,j]) else 0 ))))
  + }
  > nodeicov <- function(m, x){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(k) if(length(unique(c(i,j,k)))==3) (m[i,j]>m[i,k])*(x[j]-x[k]) else 0 ))))
  + }
  > edgecov <- function(m, x){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(k) if(length(unique(c(i,j,k)))==3) (m[i,j]>m[i,k])*(x[i,j]-x[i,k]) else 0 ))))
  + }
  > inconsistency <- function(m, x, w=array(1,c(nrow(m),ncol(m),ncol(m)))){
  +   n <- nrow(m)
  +   sum(sapply(1:n, function(i) sapply(1:n, function(j) sapply(1:n, function(k) if(length(unique(c(i,j,k)))==3) ((m[i,j]>m[i,k])*(x[i,j]<=x[i,k])+(m[i,j]<=m[i,k])*(x[i,j]>x[i,k]))*(w[i,j,k]) else 0 ))))
  + }
  > n <- 7
  > S <- 10
  > 
  > nw0 <- network.initialize(n,dir=TRUE)
  > nw0[,, names.eval="r", add.edges=TRUE] <- m0 <- matrix(sample.int(n, n*n, replace=TRUE), n, n)
  > nw0 %v% "v" <- xv <- rnorm(n)
  > nw0 %n% "m" <- xm <- matrix(rnorm(n*n),n,n)
  > nw0 %n% "a" <- xa <- array(rnorm(n*n*n),c(n,n,n))
  > 
  > nws <- simulate(nw0~rank.nonconformity("all")+
  +                   rank.nonconformity("local1")+
  +                   rank.nonconformity("local2")+
  +                   rank.nonconformity("localAND")+
  +                   rank.deference+
  +                   rank.nodeicov("v")+
  +                   rank.edgecov("m")+
  +                   rank.inconsistency(nw0,"r",xa),
  +                 coef=rep(0,8),response="r", reference=~DiscUnif(1, n-1), nsim=S, statsonly=FALSE)
  Best valid proposal 'DiscUnif' cannot take into account hint(s) 'sparse'.
  Error in as.list(defaultvalues) : 
    argument "response" is missing, with no default
  Calls: simulate ... eval -> eval -> <Anonymous> -> check.ErgmTerm -> as.list
  In addition: Warning message:
  Use of 'statsonly=' argument has been deprecated. Use 'output='stats'' instead. 
  Execution halted