Running 'gam-smooth-match.R' [3s]
  Running 'gam.R' [3s]
  Running 'glm.R' [2s]
  Running 'glm.nb.R' [3s]
  Running 'misc-tests.R' [2s]
  Running 'multinom.R' [2s]
  Running 'nlme.R' [3s]
  Running 'parallel.R' [2s]
  Running 'quasibinomial.R' [2s]
  Running 'rlm.R' [2s]
  Running 'singularities.R' [2s]
  Running 'survival.R' [2s]
Running the tests in 'tests/parallel.R' failed.
Complete output:
  > if(MuMIn:::.parallelPkgCheck(quiet = TRUE)) {
  + 	clusterType <- if(length(find.package("snow", quiet = TRUE))) "SOCK" else "PSOCK"
  + 	clust <- try(makeCluster(getOption("cl.cores", 2), type = clusterType))
  + 	if(inherits(clust, "cluster")) {
  + 	
  + 		library(MuMIn)
  + 		library(nlme)
  + 
  + 		data(Orthodont, package = "nlme")
  + 		#Orthodont <- Orthodont[sample.int(nrow(Orthodont), size = 64,
  + 			#replace = TRUE), ]
  + 		Orthodont$rand1 <- runif(nrow(Orthodont))
  + 		Orthodont$rand2 <- runif(nrow(Orthodont))
  + 		clusterExport(clust, "Orthodont")
  + 		clusterCall(clust, "library", "nlme", character.only = TRUE)		
  + 
  + 		# fm2 <- lmer(log(distance) ~ rand*Sex*age + (1|Subject) + (1|Sex),
  + 		#	data = Orthodont, REML=FALSE)
  + 		fm2 <- lme(log(distance) ~ rand1*Sex*age + rand2, ~ 1|Subject / Sex,
  + 			data = Orthodont, method = "ML")
  + 		print(system.time(pdd1 <- dredge(fm2, cluster = FALSE)))
  + 		print(system.time(pddc <- dredge(fm2, cluster = clust)))
  + 		print(system.time(dd1 <- dredge(fm2)))
  + 
  + 		print(pddc)
  + 		print(pdd1)
  + 		print(dd1)
  + 		
  + 		#print(all.equal(pddc, dd1))
  + 		ma1 <- model.avg(pdd1, beta = "none")
  + 		ma0 <- model.avg(pddc)
  + 
  + 		if(!isTRUE(test <- all.equal(ma1$avg.model, ma0$avg.model))) {
  + 			print(test)
  + 			warning("'ma1' and 'ma0' are not equal")
  + 		}
  + 		if(!isTRUE(test <- all.equal(ma1$summary, ma0$summary))) {
  + 			print(test)
  + 			warning("'ma1' and 'ma0' are not equal")
  + 		}
  + 		
  +         if(!(identical(c(pddc), c(pdd1)) && identical(c(pdd1), c(dd1)))) {
  + 		    warning("results of 'dredge' and 'pdredge' are not equal")
  + 			print(all.equal(c(pddc), c(pdd1)))
  + 			print(all.equal(c(pdd1), c(dd1)))
  + 		}
  + 
  + 		stopCluster(clust)
  + 
  + 	# suppressPackageStartupMessages(library(spdep))
  + 	# suppressMessages(example(NY_data, echo = FALSE))
  + 	# esar1f <- spautolm(Z ~ PEXPOSURE * PCTAGE65P + PCTOWNHOME,
  + 	# data=nydata, listw=listw_NY, family="SAR", method="full", verbose=FALSE)
  + 	# clusterCall(clust, "library", "spdep", character.only = TRUE)
  + 	# clusterExport(clust, "listw_NY", "nydata")
  + 	# options(warn=1)
  + 
  + 	# varying <- list(family = list("CAR", "SAR"), method=list("Matrix_J", "full"))
  + 
  + 	# dd <- dredge(esar1f, m.lim=c(0, 1),  fixed=~PEXPOSURE, varying = varying, trace=FALSE)
  + 
  + 	} else # if(inherits(clust, "try-error"))
  + 	message("Could not set up the cluster")
  + 
  + }
  Error in solve.default(-val) : 
    system is computationally singular: reciprocal condition number = 1.45557e-35
  Calls: lme -> lme.formula -> lmeApVar -> solve -> solve.default
  Execution halted