R Under development (unstable) (2022-04-07 r82109) -- "Unsuffered Consequences"
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> 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-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:188:26: runtime error: reference binding to null pointer of type 'double'
    #0 0x7fcc4dcd5b05 in Eigen::PlainObjectBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::coeffRef(long, long) /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:188:9
    #1 0x7fcc4dcd375e 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-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:509:44
    #2 0x7fcc4dcd2a1b in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute() /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:3
    #3 0x7fcc4dcd25f5 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-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:131:7
    #4 0x7fcc4dcd249b 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-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:323:3
    #5 0x7fcc4dcd224c in Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::partialPivLu() const /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:594:10
    #6 0x7fcc4dcd20f1 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-clang/RcppEigen/include/Eigen/src/LU/InverseImpl.h:28:21
    #7 0x7fcc4de02359 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-clang/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:3
    #8 0x7fcc4de02359 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<!(evaluator_assume_aliasing<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >::value), void*>::type) /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:804:3
    #9 0x7fcc4de02359 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-clang/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:782:3
    #10 0x7fcc4de0229d 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-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:714:7
    #11 0x7fcc4ddeafe6 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-clang/RcppEigen/include/Eigen/src/Core/Matrix.h:225:20
    #12 0x7fcc4ddeafe6 in MultiNormal::setPrecision(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/MultiNormal.cpp:55:13
    #13 0x7fcc4ddeae3a 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-clang-SAN/glmmsr/src/MultiNormal.cpp:22:3
    #14 0x7fcc4de09f4b in NormalBelief::NormalBelief(std::__1::vector<int, std::__1::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/NormalBelief.cpp:19:3
    #15 0x7fcc4ddd6af5 in MixedContinuousBelief::MixedContinuousBelief(std::__1::vector<int, std::__1::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/MixedContinuousBelief.cpp:17:51
    #16 0x7fcc4dd5ef9a in ClusterGraph::initializeInternal(Graph&, std::__1::vector<int, std::__1::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/ClusterGraph.cpp:254:22
    #17 0x7fcc4dd5ddd6 in ClusterGraph::initialize(Graph const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/ClusterGraph.cpp:36:3
    #18 0x7fcc4dd5d956 in ClusterGraph::ClusterGraph(std::__1::vector<MixedContinuousBelief, std::__1::allocator<MixedContinuousBelief> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/ClusterGraph.cpp:27:3
    #19 0x7fcc4de79a59 in cluster_graph__ctor(std::__1::vector<MixedContinuousBelief, std::__1::allocator<MixedContinuousBelief> >) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/RcppR6.cpp:82:10
    #20 0x7fcc4de4917b in _glmmsr_cluster_graph__ctor /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/RcppExports.cpp:210:34
    #21 0x6e724f in R_doDotCall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:601:17
    #22 0x732af9 in do_dotcall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:1284:11
    #23 0x8427a5 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7136:14
    #24 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #25 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #26 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #27 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #28 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #29 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #30 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #31 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #32 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #33 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #34 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #35 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #36 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #37 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #38 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #39 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #40 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #41 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #42 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #43 0x82db88 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:871:12
    #44 0x8a1ac1 in do_set /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2991:8
    #45 0x82d538 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:823:12
    #46 0x88efe0 in Rf_evalList /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:3089:12
    #47 0x82d733 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:842:6
    #48 0x95c7d6 in Rf_ReplIteration /data/gannet/ripley/R/svn/R-devel/src/main/main.c:264:2
    #49 0x95fd30 in R_ReplConsole /data/gannet/ripley/R/svn/R-devel/src/main/main.c:316:11
    #50 0x95fb39 in run_Rmainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1137:5
    #51 0x95fe72 in Rf_mainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1144:5
    #52 0x4f30ba in main /data/gannet/ripley/R/svn/R-devel/src/main/Rmain.c:29:5
    #53 0x7fcc5dcd9b74 in __libc_start_main (/lib64/libc.so.6+0x27b74) (BuildId: 08df60634339b221bb854d4e10b7278cafde70c4)
    #54 0x43231d in _start (/data/gannet/ripley/R/R-clang-SAN/bin/exec/R+0x43231d)

SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:188:26 in 
/data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:198:24: runtime error: reference binding to null pointer of type 'int'
    #0 0x7fcc4dcd5bb6 in Eigen::PlainObjectBase<Eigen::Matrix<int, -1, 1, 0, -1, 1> >::coeffRef(long) /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:198:7
    #1 0x7fcc4dcd5bb6 in Eigen::TranspositionsBase<Eigen::Transpositions<-1, -1, int> >::coeffRef(long) /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/Transpositions.h:47:63
    #2 0x7fcc4dcd3776 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-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:509:97
    #3 0x7fcc4dcd2a1b in Eigen::PartialPivLU<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::compute() /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:3
    #4 0x7fcc4dcd25f5 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-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:131:7
    #5 0x7fcc4dcd249b 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-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:323:3
    #6 0x7fcc4dcd224c in Eigen::MatrixBase<Eigen::Matrix<double, -1, -1, 0, -1, -1> >::partialPivLu() const /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:594:10
    #7 0x7fcc4dcd20f1 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-clang/RcppEigen/include/Eigen/src/LU/InverseImpl.h:28:21
    #8 0x7fcc4de02359 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-clang/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:3
    #9 0x7fcc4de02359 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<!(evaluator_assume_aliasing<Eigen::Inverse<Eigen::Matrix<double, -1, -1, 0, -1, -1> > >::value), void*>::type) /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:804:3
    #10 0x7fcc4de02359 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-clang/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:782:3
    #11 0x7fcc4de0229d 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-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:714:7
    #12 0x7fcc4ddeafe6 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-clang/RcppEigen/include/Eigen/src/Core/Matrix.h:225:20
    #13 0x7fcc4ddeafe6 in MultiNormal::setPrecision(Eigen::Matrix<double, -1, -1, 0, -1, -1> const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/MultiNormal.cpp:55:13
    #14 0x7fcc4ddeae3a 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-clang-SAN/glmmsr/src/MultiNormal.cpp:22:3
    #15 0x7fcc4de09f4b in NormalBelief::NormalBelief(std::__1::vector<int, std::__1::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/NormalBelief.cpp:19:3
    #16 0x7fcc4ddd6af5 in MixedContinuousBelief::MixedContinuousBelief(std::__1::vector<int, std::__1::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/MixedContinuousBelief.cpp:17:51
    #17 0x7fcc4dd5ef9a in ClusterGraph::initializeInternal(Graph&, std::__1::vector<int, std::__1::allocator<int> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/ClusterGraph.cpp:254:22
    #18 0x7fcc4dd5ddd6 in ClusterGraph::initialize(Graph const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/ClusterGraph.cpp:36:3
    #19 0x7fcc4dd5d956 in ClusterGraph::ClusterGraph(std::__1::vector<MixedContinuousBelief, std::__1::allocator<MixedContinuousBelief> > const&) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/ClusterGraph.cpp:27:3
    #20 0x7fcc4de79a59 in cluster_graph__ctor(std::__1::vector<MixedContinuousBelief, std::__1::allocator<MixedContinuousBelief> >) /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/RcppR6.cpp:82:10
    #21 0x7fcc4de4917b in _glmmsr_cluster_graph__ctor /data/gannet/ripley/R/packages/tests-clang-SAN/glmmsr/src/RcppExports.cpp:210:34
    #22 0x6e724f in R_doDotCall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:601:17
    #23 0x732af9 in do_dotcall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:1284:11
    #24 0x8427a5 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7136:14
    #25 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #26 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #27 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #28 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #29 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #30 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #31 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #32 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #33 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #34 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #35 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #36 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #37 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #38 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #39 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #40 0x8520df in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7104:12
    #41 0x82d14e in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748:8
    #42 0x8959c3 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c
    #43 0x89166f in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844:16
    #44 0x82db88 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:871:12
    #45 0x8a1ac1 in do_set /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2991:8
    #46 0x82d538 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:823:12
    #47 0x88efe0 in Rf_evalList /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:3089:12
    #48 0x82d733 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:842:6
    #49 0x95c7d6 in Rf_ReplIteration /data/gannet/ripley/R/svn/R-devel/src/main/main.c:264:2
    #50 0x95fd30 in R_ReplConsole /data/gannet/ripley/R/svn/R-devel/src/main/main.c:316:11
    #51 0x95fb39 in run_Rmainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1137:5
    #52 0x95fe72 in Rf_mainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1144:5
    #53 0x4f30ba in main /data/gannet/ripley/R/svn/R-devel/src/main/Rmain.c:29:5
    #54 0x7fcc5dcd9b74 in __libc_start_main (/lib64/libc.so.6+0x27b74) (BuildId: 08df60634339b221bb854d4e10b7278cafde70c4)
    #55 0x43231d in _start (/data/gannet/ripley/R/R-clang-SAN/bin/exec/R+0x43231d)

SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior /data/gannet/ripley/R/test-clang/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:198:24 in 
Approximating the likelihood at each point takes 0.456 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:  82.692 2.429 264.779 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')