R Under development (unstable) (2022-04-08 r82135) -- "Unsuffered Consequences"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> pkgname <- "glmmsr"
> source(file.path(R.home("share"), "R", "examples-header.R"))
> options(warn = 1)
> library('glmmsr')
> 
> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
> base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
> cleanEx()
> nameEx("glmm")
> ### * glmm
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: glmm
> ### Title: Fit a GLMM
> ### Aliases: glmm
> 
> ### ** Examples
> 
> # Fit a three-level model with the Laplace approximation to the likelihood
> (mod_Laplace <- glmm(response ~ covariate + (1 | cluster) + (1 | group),
+                      data = three_level, family = binomial,
+                      method = "Laplace"))
Fitting the model. done.
Generalized linear mixed model fit by maximum likelihood [glmmFit] 
Likelihood approximation: Laplace approximation, order  1 
 
Family: binomial ( logit ) 
Formula: response ~ covariate + (1 | cluster) + (1 | group)

Random effects:
  Groups  Name        Estimate
1 cluster (Intercept) 0.3576  
2 group   (Intercept) 0.4257  
Number of obs: 200, groups: cluster, 100; group, 50; 
 
Fixed effects: 
(Intercept)   covariate 
    -0.1909      0.1199 
> 
> # if we try to fit with adaptive Gaussian quadrature, we get an error
> ## Not run: 
> ##D   (mod_AGQ <- glmm(response ~ covariate + (1 | cluster) + (1 | group),
> ##D                    data = three_level, family = binomial, method = "AGQ",
> ##D                    control = list(nAGQ = 15)))
> ## End(Not run)
> 
> # We can fit with the Sequential Reduction approximation
> ## Not run: 
> ##D   (mod_SR <- glmm(response ~ covariate + (1 | cluster) + (1 | group),
> ##D                   data = three_level, family = binomial, method = "SR",
> ##D                   control = list(nSL = 3)))
> ## End(Not run)
> # the estimates of the random effects standard deviations
> # are larger than those using the Laplace approximation
> 
> 
> 
> cleanEx()
> nameEx("three_level")
> ### * three_level
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: three_level
> ### Title: A dataset simulated from a three-level model
> ### Aliases: three_level
> ### Keywords: datasets
> 
> ### ** Examples
> 
> # Fit a three-level model with the Laplace approximation to the likelihood
> (mod_Laplace <- glmm(response ~ covariate + (1 | cluster) + (1 | group),
+                      data = three_level, family = binomial,
+                      method = "Laplace"))
Fitting the model. done.
Generalized linear mixed model fit by maximum likelihood [glmmFit] 
Likelihood approximation: Laplace approximation, order  1 
 
Family: binomial ( logit ) 
Formula: response ~ covariate + (1 | cluster) + (1 | group)

Random effects:
  Groups  Name        Estimate
1 cluster (Intercept) 0.3576  
2 group   (Intercept) 0.4257  
Number of obs: 200, groups: cluster, 100; group, 50; 
 
Fixed effects: 
(Intercept)   covariate 
    -0.1909      0.1199 
> 
> # if we try to fit with adaptive Gaussian quadrature, we get an error
> ## Not run: 
> ##D   (mod_AGQ <- glmm(response ~ covariate + (1 | cluster) + (1 | group),
> ##D                    data = three_level, family = binomial, method = "AGQ",
> ##D                    control = list(nAGQ = 15)))
> ## End(Not run)
> 
> # We can fit with the Sequential Reduction approximation
> ## Not run: 
> ##D   (mod_SR <- glmm(response ~ covariate + (1 | cluster) + (1 | group),
> ##D                   data = three_level, family = binomial, method = "SR",
> ##D                   control = list(nSL = 3)))
> ## End(Not run)
> # the estimates of the random effects standard deviations
> # are larger than those using the Laplace approximation
> 
> 
> 
> cleanEx()
> nameEx("two_level")
> ### * two_level
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: two_level
> ### Title: A dataset simulated from a two-level model
> ### Aliases: two_level
> ### Keywords: datasets
> 
> ### ** Examples
> 
> # Fit a two-level model with the Laplace approximation to the likelihood
> (mod_Laplace <- glmm(response ~ covariate + (1 | cluster), data = two_level,
+                      family = binomial, method = "Laplace"))
Fitting the model. done.
Generalized linear mixed model fit by maximum likelihood [glmmFit] 
Likelihood approximation: Laplace approximation, order  1 
 
Family: binomial ( logit ) 
Formula: response ~ covariate + (1 | cluster)

Random effects:
  Groups  Name        Estimate
1 cluster (Intercept) 0.7484  
Number of obs: 100, groups: cluster, 50; 
 
Fixed effects: 
(Intercept)   covariate 
     0.6525     -1.1583 
> 
> # or with adaptive Gaussian quadrature
> (mod_AGQ <- glmm(response ~ covariate + (1 | cluster), data = two_level,
+                  family = binomial, method = "AGQ", control = list(nAGQ = 15)))
Fitting the model. done.
Generalized linear mixed model fit by maximum likelihood [glmmFit] 
Likelihood approximation: Adaptive Gaussian Quadrature with 15 points (lme4) 
 
Family: binomial ( logit ) 
Formula: response ~ covariate + (1 | cluster)

Random effects:
  Groups  Name        Estimate
1 cluster (Intercept) 1.041   
Number of obs: 100, groups: cluster, 50; 
 
Fixed effects: 
(Intercept)   covariate 
     0.7168     -1.2734 
> 
> # or with the Sequential Reduction approximation
> (mod_SR <- glmm(response ~ covariate + (1 | cluster), data = two_level,
+                 family = binomial, method = "SR", control = list(nSL = 3)))
/data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:198:30: runtime error: reference binding to null pointer of type 'Scalar'
    #0 0x7efc48e1785c in Eigen::PlainObjectBase<Eigen::Matrix<int, -1, 1, 0, -1, 1> >::coeffRef(long) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:198
    #1 0x7efc48e1785c in Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> >::coeffRef(long) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/Transpositions.h:47
    #2 0x7efc48e1785c in void Eigen::internal::partial_lu_inplace<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Transpositions<-1, -1, int> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Transpositions<-1, -1, int>&, Eigen::Transpositions<-1, -1, int>::StorageIndex&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:509
    #3 0x7efc48e1785c in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute() /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533
    #4 0x7efc48e1a1fa in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >& Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute<Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::EigenBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:131
    #5 0x7efc48e1a1fa in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::EigenBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:323
    #6 0x7efc4919a3de in Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::partialPivLu() const /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:594
    #7 0x7efc4919a3de in Eigen::internal::compute_inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, -1>::run(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&, Eigen::Matrix<double, -1, -1, 0, -1, -1>&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/InverseImpl.h:28
    #8 0x7efc4919a3de in Eigen::internal::Assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double>, Eigen::internal::Dense2Dense, void>::run(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/InverseImpl.h:310
    #9 0x7efc491aa2bd in void Eigen::internal::call_assignment_no_alias<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836
    #10 0x7efc491aa2bd in void Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&, Eigen::internal::enable_if<!Eigen::internal::evaluator_assume_aliasing<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::evaluator_traits<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >::Shape>::value, void*>::type) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:804
    #11 0x7efc491aa2bd in void Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:782
    #12 0x7efc491aa2bd in Eigen::Matrix<double, -1, -1, 0, -1, -1>& Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::_set<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::DenseBase<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:714
    #13 0x7efc491aa2bd in Eigen::Matrix<double, -1, -1, 0, -1, -1>& Eigen::Matrix<double, -1, -1, 0, -1, -1>::operator=<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::DenseBase<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/Matrix.h:225
    #14 0x7efc491aa2bd in MultiNormal::setPrecision(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MultiNormal.cpp:55
    #15 0x7efc491ae1bb in MultiNormal::MultiNormal(Eigen::Matrix<double, -1, 1, 0, -1, 1> const&, Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MultiNormal.cpp:22
    #16 0x7efc49222adc in NormalBelief::NormalBelief(std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/NormalBelief.cpp:19
    #17 0x7efc49121987 in MixedContinuousBelief::MixedContinuousBelief(std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MixedContinuousBelief.cpp:17
    #18 0x7efc48f0c002 in ClusterGraph::initializeInternal(Graph&, std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:254
    #19 0x7efc48f114ca in ClusterGraph::initialize(Graph const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:36
    #20 0x7efc48f128ce in ClusterGraph::ClusterGraph(std::vector<MixedContinuousBelief, std::allocator<MixedContinuousBelief> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:27
    #21 0x7efc493add91 in cluster_graph__ctor(std::vector<MixedContinuousBelief, std::allocator<MixedContinuousBelief> >) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/RcppR6.cpp:82
    #22 0x7efc493457cb in _glmmsr_cluster_graph__ctor /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/RcppExports.cpp:210
    #23 0x5818a3 in R_doDotCall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:601
    #24 0x589d5c in do_dotcall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:1284
    #25 0x62d766 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7136
    #26 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #27 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #28 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #29 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #30 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #31 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #32 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #33 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #34 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #35 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #36 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #37 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #38 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #39 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #40 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #41 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #42 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #43 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #44 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #45 0x67569f in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:871
    #46 0x681779 in do_set /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2991
    #47 0x675ac0 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:823
    #48 0x681b52 in Rf_evalList /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:3089
    #49 0x675d1b in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:842
    #50 0x6f765d in Rf_ReplIteration /data/gannet/ripley/R/svn/R-devel/src/main/main.c:264
    #51 0x6f7cf0 in R_ReplConsole /data/gannet/ripley/R/svn/R-devel/src/main/main.c:316
    #52 0x6f7e34 in run_Rmainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1137
    #53 0x6f7e82 in Rf_mainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1144
    #54 0x41b418 in main /data/gannet/ripley/R/svn/R-devel/src/main/Rmain.c:29
    #55 0x7efc5ae95b74 in __libc_start_main (/lib64/libc.so.6+0x27b74)
    #56 0x41dc1d in _start (/data/gannet/ripley/R/gcc-SAN/bin/exec/R+0x41dc1d)

/data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/Transpositions.h:47:73: runtime error: reference binding to null pointer of type 'StorageIndex'
    #0 0x7efc48e1781e in Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> >::coeffRef(long) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/Transpositions.h:47
    #1 0x7efc48e1781e in void Eigen::internal::partial_lu_inplace<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Transpositions<-1, -1, int> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Transpositions<-1, -1, int>&, Eigen::Transpositions<-1, -1, int>::StorageIndex&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:509
    #2 0x7efc48e1781e in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute() /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533
    #3 0x7efc48e1a1fa in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >& Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute<Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::EigenBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:131
    #4 0x7efc48e1a1fa in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::EigenBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:323
    #5 0x7efc4919a3de in Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::partialPivLu() const /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:594
    #6 0x7efc4919a3de in Eigen::internal::compute_inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, -1>::run(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&, Eigen::Matrix<double, -1, -1, 0, -1, -1>&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/InverseImpl.h:28
    #7 0x7efc4919a3de in Eigen::internal::Assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double>, Eigen::internal::Dense2Dense, void>::run(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/InverseImpl.h:310
    #8 0x7efc491aa2bd in void Eigen::internal::call_assignment_no_alias<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836
    #9 0x7efc491aa2bd in void Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&, Eigen::internal::enable_if<!Eigen::internal::evaluator_assume_aliasing<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::evaluator_traits<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >::Shape>::value, void*>::type) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:804
    #10 0x7efc491aa2bd in void Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:782
    #11 0x7efc491aa2bd in Eigen::Matrix<double, -1, -1, 0, -1, -1>& Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::_set<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::DenseBase<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:714
    #12 0x7efc491aa2bd in Eigen::Matrix<double, -1, -1, 0, -1, -1>& Eigen::Matrix<double, -1, -1, 0, -1, -1>::operator=<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::DenseBase<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/Matrix.h:225
    #13 0x7efc491aa2bd in MultiNormal::setPrecision(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MultiNormal.cpp:55
    #14 0x7efc491ae1bb in MultiNormal::MultiNormal(Eigen::Matrix<double, -1, 1, 0, -1, 1> const&, Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MultiNormal.cpp:22
    #15 0x7efc49222adc in NormalBelief::NormalBelief(std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/NormalBelief.cpp:19
    #16 0x7efc49121987 in MixedContinuousBelief::MixedContinuousBelief(std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MixedContinuousBelief.cpp:17
    #17 0x7efc48f0c002 in ClusterGraph::initializeInternal(Graph&, std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:254
    #18 0x7efc48f114ca in ClusterGraph::initialize(Graph const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:36
    #19 0x7efc48f128ce in ClusterGraph::ClusterGraph(std::vector<MixedContinuousBelief, std::allocator<MixedContinuousBelief> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:27
    #20 0x7efc493add91 in cluster_graph__ctor(std::vector<MixedContinuousBelief, std::allocator<MixedContinuousBelief> >) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/RcppR6.cpp:82
    #21 0x7efc493457cb in _glmmsr_cluster_graph__ctor /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/RcppExports.cpp:210
    #22 0x5818a3 in R_doDotCall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:601
    #23 0x589d5c in do_dotcall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:1284
    #24 0x62d766 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7136
    #25 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #26 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #27 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #28 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #29 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #30 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #31 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #32 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #33 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #34 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #35 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #36 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #37 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #38 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #39 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #40 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #41 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #42 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #43 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #44 0x67569f in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:871
    #45 0x681779 in do_set /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2991
    #46 0x675ac0 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:823
    #47 0x681b52 in Rf_evalList /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:3089
    #48 0x675d1b in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:842
    #49 0x6f765d in Rf_ReplIteration /data/gannet/ripley/R/svn/R-devel/src/main/main.c:264
    #50 0x6f7cf0 in R_ReplConsole /data/gannet/ripley/R/svn/R-devel/src/main/main.c:316
    #51 0x6f7e34 in run_Rmainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1137
    #52 0x6f7e82 in Rf_mainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1144
    #53 0x41b418 in main /data/gannet/ripley/R/svn/R-devel/src/main/Rmain.c:29
    #54 0x7efc5ae95b74 in __libc_start_main (/lib64/libc.so.6+0x27b74)
    #55 0x41dc1d in _start (/data/gannet/ripley/R/gcc-SAN/bin/exec/R+0x41dc1d)

/data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:188:32: runtime error: reference binding to null pointer of type 'Scalar'
    #0 0x7efc48e17e1e in Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::coeffRef(long, long) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:188
    #1 0x7efc48e17e1e in void Eigen::internal::partial_lu_inplace<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Transpositions<-1, -1, int> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Transpositions<-1, -1, int>&, Eigen::Transpositions<-1, -1, int>::StorageIndex&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:509
    #2 0x7efc48e17e1e in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute() /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533
    #3 0x7efc48e1a1fa in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >& Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute<Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::EigenBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:131
    #4 0x7efc48e1a1fa in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >(Eigen::EigenBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:323
    #5 0x7efc4919a3de in Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::partialPivLu() const /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:594
    #6 0x7efc4919a3de in Eigen::internal::compute_inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Matrix<double, -1, -1, 0, -1, -1>, -1>::run(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&, Eigen::Matrix<double, -1, -1, 0, -1, -1>&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/InverseImpl.h:28
    #7 0x7efc4919a3de in Eigen::internal::Assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double>, Eigen::internal::Dense2Dense, void>::run(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/LU/InverseImpl.h:310
    #8 0x7efc491aa2bd in void Eigen::internal::call_assignment_no_alias<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836
    #9 0x7efc491aa2bd in void Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::assign_op<double, double> >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&, Eigen::internal::assign_op<double, double> const&, Eigen::internal::enable_if<!Eigen::internal::evaluator_assume_aliasing<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> >, Eigen::internal::evaluator_traits<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >::Shape>::value, void*>::type) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:804
    #10 0x7efc491aa2bd in void Eigen::internal::call_assignment<Eigen::Matrix<double, -1, -1, 0, -1, -1>, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::Matrix<double, -1, -1, 0, -1, -1>&, Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:782
    #11 0x7efc491aa2bd in Eigen::Matrix<double, -1, -1, 0, -1, -1>& Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::_set<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::DenseBase<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:714
    #12 0x7efc491aa2bd in Eigen::Matrix<double, -1, -1, 0, -1, -1>& Eigen::Matrix<double, -1, -1, 0, -1, -1>::operator=<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >(Eigen::DenseBase<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > > const&) /data/gannet/ripley/R/test-dev/RcppEigen/include/Eigen/src/Core/Matrix.h:225
    #13 0x7efc491aa2bd in MultiNormal::setPrecision(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MultiNormal.cpp:55
    #14 0x7efc491ae1bb in MultiNormal::MultiNormal(Eigen::Matrix<double, -1, 1, 0, -1, 1> const&, Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MultiNormal.cpp:22
    #15 0x7efc49222adc in NormalBelief::NormalBelief(std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/NormalBelief.cpp:19
    #16 0x7efc49121987 in MixedContinuousBelief::MixedContinuousBelief(std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/MixedContinuousBelief.cpp:17
    #17 0x7efc48f0c002 in ClusterGraph::initializeInternal(Graph&, std::vector<int, std::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:254
    #18 0x7efc48f114ca in ClusterGraph::initialize(Graph const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:36
    #19 0x7efc48f128ce in ClusterGraph::ClusterGraph(std::vector<MixedContinuousBelief, std::allocator<MixedContinuousBelief> > const&) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/ClusterGraph.cpp:27
    #20 0x7efc493add91 in cluster_graph__ctor(std::vector<MixedContinuousBelief, std::allocator<MixedContinuousBelief> >) /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/RcppR6.cpp:82
    #21 0x7efc493457cb in _glmmsr_cluster_graph__ctor /data/gannet/ripley/R/packages/tests-gcc-SAN/glmmsr/src/RcppExports.cpp:210
    #22 0x5818a3 in R_doDotCall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:601
    #23 0x589d5c in do_dotcall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:1284
    #24 0x62d766 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7136
    #25 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #26 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #27 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #28 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #29 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #30 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #31 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #32 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #33 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #34 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #35 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #36 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #37 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #38 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #39 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #40 0x64c745 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104
    #41 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #42 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #43 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #44 0x67569f in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:871
    #45 0x681779 in do_set /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2991
    #46 0x675ac0 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:823
    #47 0x681b52 in Rf_evalList /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:3089
    #48 0x675d1b in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:842
    #49 0x6f765d in Rf_ReplIteration /data/gannet/ripley/R/svn/R-devel/src/main/main.c:264
    #50 0x6f7cf0 in R_ReplConsole /data/gannet/ripley/R/svn/R-devel/src/main/main.c:316
    #51 0x6f7e34 in run_Rmainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1137
    #52 0x6f7e82 in Rf_mainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1144
    #53 0x41b418 in main /data/gannet/ripley/R/svn/R-devel/src/main/Rmain.c:29
    #54 0x7efc5ae95b74 in __libc_start_main (/lib64/libc.so.6+0x27b74)
    #55 0x41dc1d in _start (/data/gannet/ripley/R/gcc-SAN/bin/exec/R+0x41dc1d)

Approximating the likelihood at each point takes 0.363 seconds. 
Fitting the model........................................... done.
Generalized linear mixed model fit by maximum likelihood [glmmFit] 
Likelihood approximation: Sequential reduction at level 3 
 
Family: binomial ( logit ) 
Formula: response ~ covariate + (1 | cluster)

Random effects:
  Groups  Name        Estimate
1 cluster (Intercept) 1.041   
Number of obs: 100, groups: cluster, 50; 
 
Fixed effects: 
(Intercept)   covariate 
     0.7168     -1.2734 
> 
> # in a two-level model, method = "SR" is equivalent to method = "AGQ" with
> # nAGQ = 2^(nSL+1) - 1
> 
> 
> 
> ### * <FOOTER>
> ###
> cleanEx()
> options(digits = 7L)
> base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
Time elapsed:  60.257 1.977 138.99 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')