Error Message in Running "rstan"

[zelmously]

In running the “rstan” package in R, I get the error message below.

Error in inDL(x, as.logical(local), as.logical(now), …) :
unable to load shared object ‘C:/Users/ziad.elmously/AppData/Local/Temp/Rtmpu4QFtu/file7043ca567a9.dll’:
LoadLibrary failure: A dynamic link library (DLL) initialization routine failed.
In addition: Warning message:
In system(paste(CXX, ARGS), ignore.stdout = TRUE, ignore.stderr = TRUE) :
‘C:/rtools40/usr/mingw_/bin/g++’ not found
Error in sink(type = “output”) : invalid connection

This is the sample script I am trying to run.

library(rstan)
bern.stan =
"
data {
int<lower=0> N; // number of trials
int<lower=0, upper=1> y[N]; // success on trial n
}
parameters {
real<lower=0, upper=1> theta; // chance of success
}
model {
theta ~ uniform(0, 1); // prior
y ~ bernoulli(theta); // likelihood
}
"

Generate data

theta = 0.30
N = 20
y = rbinom(N, 1, 0.3)
y
sum(y) / N
fit = stan(model_code=bern.stan, data=list(y=y, N=N), iter=5000)

Thank you in advance.

[andrjohns]

Can you restart R (making sure that rstan doesn’t get loaded) and try reinstalling from source:

# Compile packages using all cores
Sys.setenv(MAKEFLAGS = paste0("-j",parallel::detectCores()))

install.packages(c("StanHeaders","rstan"),type="source")

There might a lot of compiler warnings, but they’re safe to ignore

[zelmously]

Many thanks for the advice. I tried it, but it did not solve the problem.

[andrjohns]

What do you get if you run:

example(stan_model, package="rstan",run.dontrun=T)

[zelmously]

I get a lot of output, and then I get the same error message as before.

stn_md> stancode ← ‘data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}’

stn_md> mod ← stan_model(model_code = stancode, verbose = TRUE)

TRANSLATING MODEL ‘73fc79f8b1915e8208c736914c86d1a1’ FROM Stan CODE TO C++ CODE NOW.
successful in parsing the Stan model ‘73fc79f8b1915e8208c736914c86d1a1’.
COMPILING THE C++ CODE FOR MODEL ‘73fc79f8b1915e8208c736914c86d1a1’ NOW.
OS: x86_64, mingw32; rstan: 2.21.2; Rcpp: 1.0.7; inline: 0.3.19

setting environment variables:
LOCAL_LIBS = “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/rstan/lib/x64/libStanServices.a” -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/libs/x64" -lStanHeaders -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppParallel/lib/x64" -ltbb
PKG_CPPFLAGS = -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/Rcpp/include/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppEigen/include/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppEigen/include/unsupported" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/BH/include" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/include/src/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/include/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppParallel/include/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/rstan/include" -DEIGEN_NO_DEBUG -DBOOST_DISABLE_ASSERTS -DBOOST_PENDING_INTEGER_LOG2_HPP -DSTAN_THREADS -DBOOST_NO_AUTO_PTR -include “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/include/stan/math/prim/mat/fun/Eigen.hpp” -std=c++1y
Program source :

1 :
2 : // includes from the plugin
3 : // [[Rcpp::plugins(cpp14)]]
4 :
5 :
6 : // user includes
7 : #include <Rcpp.h>
8 : #include <rstan/io/rlist_ref_var_context.hpp>
9 : #include <rstan/io/r_ostream.hpp>
10 : #include <rstan/stan_args.hpp>
11 : #include <boost/integer/integer_log2.hpp>
12 : // Code generated by Stan version 2.21.0
13 :
14 : #include <stan/model/model_header.hpp>
15 :
16 : namespace model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1_namespace {
17 :
18 : using std::istream;
19 : using std::string;
20 : using std::stringstream;
21 : using std::vector;
22 : using stan::io::dump;
23 : using stan::math::lgamma;
24 : using stan::model::prob_grad;
25 : using namespace stan::math;
26 :
27 : static int current_statement_begin__;
28 :
29 : stan::io::program_reader prog_reader__() {
30 : stan::io::program_reader reader;
31 : reader.add_event(0, 0, “start”, “model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1”);
32 : reader.add_event(3, 1, “end”, “model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1”);
33 : return reader;
34 : }
35 :
36 : class model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1
37 : : public stan::model::model_base_crtp<model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1> {
38 : private:
39 : double y_mean;
40 : public:
41 : model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1(rstan::io::rlist_ref_var_context& context__,
42 : std::ostream* pstream__ = 0)
43 : : model_base_crtp(0) {
44 : ctor_body(context__, 0, pstream__);
45 : }
46 :
47 : model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1(stan::io::var_context& context__,
48 : unsigned int random_seed__,
49 : std::ostream* pstream__ = 0)
50 : : model_base_crtp(0) {
51 : ctor_body(context__, random_seed__, pstream__);
52 : }
53 :
54 : void ctor_body(stan::io::var_context& context__,
55 : unsigned int random_seed__,
56 : std::ostream* pstream__) {
57 : typedef double local_scalar_t__;
58 :
59 : boost::ecuyer1988 base_rng__ =
60 : stan::services::util::create_rng(random_seed__, 0);
61 : (void) base_rng__; // suppress unused var warning
62 :
63 : current_statement_begin__ = -1;
64 :
65 : static const char* function__ = “model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1_namespace::model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1”;
66 : (void) function__; // dummy to suppress unused var warning
67 : size_t pos__;
68 : (void) pos__; // dummy to suppress unused var warning
69 : std::vector vals_i__;
70 : std::vector vals_r__;
71 : local_scalar_t__ DUMMY_VAR__(std::numeric_limits::quiet_NaN());
72 : (void) DUMMY_VAR__; // suppress unused var warning
73 :
74 : try {
75 : // initialize data block variables from context__
76 : current_statement_begin__ = 1;
77 : context__.validate_dims(“data initialization”, “y_mean”, “double”, context__.to_vec());
78 : y_mean = double(0);
79 : vals_r__ = context__.vals_r(“y_mean”);
80 : pos__ = 0;
81 : y_mean = vals_r__[pos__++];
82 :
83 :
84 : // initialize transformed data variables
85 : // execute transformed data statements
86 :
87 : // validate transformed data
88 :
89 : // validate, set parameter ranges
90 : num_params_r__ = 0U;
91 : param_ranges_i__.clear();
92 : current_statement_begin__ = 1;
93 : num_params_r__ += 1;
94 : } catch (const std::exception& e) {
95 : stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
96 : // Next line prevents compiler griping about no return
97 : throw std::runtime_error(“*** IF YOU SEE THIS, PLEASE REPORT A BUG ");
98 : }
99 : }
100 :
101 : ~model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1() { }
102 :
103 :
104 : void transform_inits(const stan::io::var_context& context__,
105 : std::vector& params_i__,
106 : std::vector& params_r__,
107 : std::ostream pstream__) const {
108 : typedef double local_scalar_t__;
109 : stan::io::writer writer__(params_r__, params_i__);
110 : size_t pos__;
111 : (void) pos__; // dummy call to supress warning
112 : std::vector vals_r__;
113 : std::vector vals_i__;
114 :
115 : current_statement_begin__ = 1;
116 : if (!(context__.contains_r(“y”)))
117 : stan::lang::rethrow_located(std::runtime_error(std::string(“Variable y missing”)), current_statement_begin__, prog_reader__());
118 : vals_r__ = context__.vals_r(“y”);
119 : pos__ = 0U;
120 : context__.validate_dims(“parameter initialization”, “y”, “double”, context__.to_vec());
121 : double y(0);
122 : y = vals_r__[pos__++];
123 : try {
124 : writer__.scalar_unconstrain(y);
125 : } catch (const std::exception& e) {
126 : stan::lang::rethrow_located(std::runtime_error(std::string("Error transforming variable y: ") + e.what()), current_statement_begin__, prog_reader__());
127 : }
128 :
129 : params_r__ = writer__.data_r();
130 : params_i__ = writer__.data_i();
131 : }
132 :
133 : void transform_inits(const stan::io::var_context& context,
134 : Eigen::Matrix<double, Eigen::Dynamic, 1>& params_r,
135 : std::ostream pstream__) const {
136 : std::vector params_r_vec;
137 : std::vector params_i_vec;
138 : transform_inits(context, params_i_vec, params_r_vec, pstream__);
139 : params_r.resize(params_r_vec.size());
140 : for (int i = 0; i < params_r.size(); ++i)
141 : params_r(i) = params_r_vec[i];
142 : }
143 :
144 :
145 : template <bool propto__, bool jacobian__, typename T__>
146 : T__ log_prob(std::vector<T__>& params_r__,
147 : std::vector& params_i__,
148 : std::ostream pstream__ = 0) const {
149 :
150 : typedef T__ local_scalar_t__;
151 :
152 : local_scalar_t__ DUMMY_VAR__(std::numeric_limits::quiet_NaN());
153 : (void) DUMMY_VAR__; // dummy to suppress unused var warning
154 :
155 : T__ lp__(0.0);
156 : stan::math::accumulator<T__> lp_accum__;
157 : try {
158 : stan::io::reader<local_scalar_t__> in__(params_r__, params_i__);
159 :
160 : // model parameters
161 : current_statement_begin__ = 1;
162 : local_scalar_t__ y;
163 : (void) y; // dummy to suppress unused var warning
164 : if (jacobian__)
165 : y = in__.scalar_constrain(lp__);
166 : else
167 : y = in__.scalar_constrain();
168 :
169 : // model body
170 :
171 : current_statement_begin__ = 1;
172 : lp_accum__.add(normal_log<propto__>(y, y_mean, 1));
173 :
174 : } catch (const std::exception& e) {
175 : stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
176 : // Next line prevents compiler griping about no return
177 : throw std::runtime_error(”*** IF YOU SEE THIS, PLEASE REPORT A BUG ");
178 : }
179 :
180 : lp_accum__.add(lp__);
181 : return lp_accum__.sum();
182 :
183 : } // log_prob()
184 :
185 : template <bool propto, bool jacobian, typename T_>
186 : T_ log_prob(Eigen::Matrix<T_,Eigen::Dynamic,1>& params_r,
187 : std::ostream pstream = 0) const {
188 : std::vector<T_> vec_params_r;
189 : vec_params_r.reserve(params_r.size());
190 : for (int i = 0; i < params_r.size(); ++i)
191 : vec_params_r.push_back(params_r(i));
192 : std::vector vec_params_i;
193 : return log_prob<propto,jacobian,T_>(vec_params_r, vec_params_i, pstream);
194 : }
195 :
196 :
197 : void get_param_names(std::vectorstd::string& names__) const {
198 : names__.resize(0);
199 : names__.push_back(“y”);
200 : }
201 :
202 :
203 : void get_dims(std::vector<std::vector<size_t> >& dimss__) const {
204 : dimss__.resize(0);
205 : std::vector<size_t> dims__;
206 : dims__.resize(0);
207 : dimss__.push_back(dims__);
208 : }
209 :
210 : template
211 : void write_array(RNG& base_rng__,
212 : std::vector& params_r__,
213 : std::vector& params_i__,
214 : std::vector& vars__,
215 : bool include_tparams__ = true,
216 : bool include_gqs__ = true,
217 : std::ostream pstream__ = 0) const {
218 : typedef double local_scalar_t__;
219 :
220 : vars__.resize(0);
221 : stan::io::reader<local_scalar_t__> in__(params_r__, params_i__);
222 : static const char function__ = “model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1_namespace::write_array”;
223 : (void) function__; // dummy to suppress unused var warning
224 :
225 : // read-transform, write parameters
226 : double y = in__.scalar_constrain();
227 : vars__.push_back(y);
228 :
229 : double lp__ = 0.0;
230 : (void) lp__; // dummy to suppress unused var warning
231 : stan::math::accumulator lp_accum__;
232 :
233 : local_scalar_t__ DUMMY_VAR__(std::numeric_limits::quiet_NaN());
234 : (void) DUMMY_VAR__; // suppress unused var warning
235 :
236 : if (!include_tparams__ && !include_gqs__) return;
237 :
238 : try {
239 : if (!include_gqs__ && !include_tparams__) return;
240 : if (!include_gqs__) return;
241 : } catch (const std::exception& e) {
242 : stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
243 : // Next line prevents compiler griping about no return
244 : throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ");
245 : }
246 : }
247 :
248 : template
249 : void write_array(RNG& base_rng,
250 : Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
251 : Eigen::Matrix<double,Eigen::Dynamic,1>& vars,
252 : bool include_tparams = true,
253 : bool include_gqs = true,
254 : std::ostream pstream = 0) const {
255 : std::vector params_r_vec(params_r.size());
256 : for (int i = 0; i < params_r.size(); ++i)
257 : params_r_vec[i] = params_r(i);
258 : std::vector vars_vec;
259 : std::vector params_i_vec;
260 : write_array(base_rng, params_r_vec, params_i_vec, vars_vec, include_tparams, include_gqs, pstream);
261 : vars.resize(vars_vec.size());
262 : for (int i = 0; i < vars.size(); ++i)
263 : vars(i) = vars_vec[i];
264 : }
265 :
266 : std::string model_name() const {
267 : return “model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1”;
268 : }
269 :
270 :
271 : void constrained_param_names(std::vectorstd::string& param_names__,
272 : bool include_tparams__ = true,
273 : bool include_gqs__ = true) const {
274 : std::stringstream param_name_stream__;
275 : param_name_stream__.str(std::string());
276 : param_name_stream__ << “y”;
277 : param_names__.push_back(param_name_stream__.str());
278 :
279 : if (!include_gqs__ && !include_tparams__) return;
280 :
281 : if (include_tparams__) {
282 : }
283 :
284 : if (!include_gqs__) return;
285 : }
286 :
287 :
288 : void unconstrained_param_names(std::vectorstd::string& param_names__,
289 : bool include_tparams__ = true,
290 : bool include_gqs__ = true) const {
291 : std::stringstream param_name_stream__;
292 : param_name_stream__.str(std::string());
293 : param_name_stream__ << “y”;
294 : param_names__.push_back(param_name_stream__.str());
295 :
296 : if (!include_gqs__ && !include_tparams__) return;
297 :
298 : if (include_tparams__) {
299 : }
300 :
301 : if (!include_gqs__) return;
302 : }
303 :
304 : }; // model
305 :
306 : } // namespace
307 :
308 : typedef model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1_namespace::model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1 stan_model;
309 :
310 : #ifndef USING_R
311 :
312 : stan::model::model_base& new_model(
313 : stan::io::var_context& data_context,
314 : unsigned int seed,
315 : std::ostream msg_stream) {
316 : stan_model m = new stan_model(data_context, seed, msg_stream);
317 : return m;
318 : }
319 :
320 : #endif
321 :
322 :
323 :
324 : #include <rstan_next/stan_fit.hpp>
325 :
326 : struct stan_model_holder {
327 : stan_model_holder(rstan::io::rlist_ref_var_context rcontext,
328 : unsigned int random_seed)
329 : : rcontext_(rcontext), random_seed_(random_seed)
330 : {
331 : }
332 :
333 : //stan::math::ChainableStack ad_stack;
334 : rstan::io::rlist_ref_var_context rcontext_;
335 : unsigned int random_seed_;
336 : };
337 :
338 : Rcpp::XPtrstan::model::model_base model_ptr(stan_model_holder smh) {
339 : Rcpp::XPtrstan::model::model_base model_instance(new stan_model(smh->rcontext_, smh->random_seed_), true);
340 : return model_instance;
341 : }
342 :
343 : Rcpp::XPtrrstan::stan_fit_base fit_ptr(stan_model_holder* smh) {
344 : return Rcpp::XPtrrstan::stan_fit_base(new rstan::stan_fit(model_ptr(smh), smh->random_seed_), true);
345 : }
346 :
347 : std::string model_name(stan_model_holder* smh) {
348 : return model_ptr(smh).get()->model_name();
349 : }
350 :
351 : RCPP_MODULE(stan_fit4model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1_mod){
352 : Rcpp::class_<stan_model_holder>(“stan_fit4model3ae02c762e14_73fc79f8b1915e8208c736914c86d1a1”)
353 : .constructor<rstan::io::rlist_ref_var_context, unsigned int>()
354 : .method(“model_ptr”, &model_ptr)
355 : .method(“fit_ptr”, &fit_ptr)
356 : .method(“model_name”, &model_name)
357 : ;
358 : }
359 :
360 :
361 : // declarations
362 : extern “C” {
363 : SEXP file3ae07613718e( ) ;
364 : }
365 :
366 : // definition
367 : SEXP file3ae07613718e() {
368 : return Rcpp::wrap(“73fc79f8b1915e8208c736914c86d1a1”);
369 : }
make cmd is
make -f “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/R-4.0.5/etc/x64/Makeconf” -f “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/R-4.0.5/share/make/winshlib.mk” CXX=‘(CXX14) (CXX14STD)’ CXXFLAGS=‘(CXX14FLAGS)' CXXPICFLAGS='(CXX14PICFLAGS)’ SHLIB_LDFLAGS=‘(SHLIB_CXX14LDFLAGS)' SHLIB_LD='(SHLIB_CXX14LD)’ SHLIB=“file3ae07613718e.dll” WIN=64 TCLBIN=64 OBJECTS=“file3ae07613718e.o”

make would use
“C:/rtools40/mingw64/bin/“g++ -std=gnu++14 -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/R-4.0.5/include” -DNDEBUG -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/Rcpp/include/” -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppEigen/include/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppEigen/include/unsupported" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/BH/include" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/include/src/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/include/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppParallel/include/" -I"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/rstan/include" -DEIGEN_NO_DEBUG -DBOOST_DISABLE_ASSERTS -DBOOST_PENDING_INTEGER_LOG2_HPP -DSTAN_THREADS -DBOOST_NO_AUTO_PTR -include “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/include/stan/math/prim/mat/fun/Eigen.hpp” -std=c++1y -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c file3ae07613718e.cpp -o file3ae07613718e.o
if test “zfile3ae07613718e.o” != “z”; then
if test -e “file3ae07613718e-win.def”; then
echo “C:/rtools40/mingw64/bin/“g++ -shared -s -static-libgcc -o file3ae07613718e.dll file3ae07613718e-win.def file3ae07613718e.o “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/rstan/lib/x64/libStanServices.a” -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/libs/x64” -lStanHeaders -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppParallel/lib/x64” -ltbb -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/R-4.0.5/bin/x64" -lR ;
“C:/rtools40/mingw64/bin/“g++ -shared -s -static-libgcc -o file3ae07613718e.dll file3ae07613718e-win.def file3ae07613718e.o “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/rstan/lib/x64/libStanServices.a” -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/libs/x64” -lStanHeaders -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppParallel/lib/x64” -ltbb -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/R-4.0.5/bin/x64" -lR ;
else
echo EXPORTS > tmp.def;
“C:/rtools40/mingw64/bin/“nm file3ae07613718e.o | sed -n ‘s/^.* [BCDRT] / /p’ | sed -e ‘/[.]refptr[.]/d’ -e ‘/[.]weak[.]/d’ | sed 's/[^ ][^ ]*/”&”/g’ >> tmp.def;
echo “C:/rtools40/mingw64/bin/“g++ -shared -s -static-libgcc -o file3ae07613718e.dll tmp.def file3ae07613718e.o “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/rstan/lib/x64/libStanServices.a” -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/libs/x64” -lStanHeaders -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppParallel/lib/x64” -ltbb -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/R-4.0.5/bin/x64" -lR ;
“C:/rtools40/mingw64/bin/“g++ -shared -s -static-libgcc -o file3ae07613718e.dll tmp.def file3ae07613718e.o “C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/rstan/lib/x64/libStanServices.a” -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/StanHeaders/libs/x64” -lStanHeaders -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/win-library/4.0/RcppParallel/lib/x64” -ltbb -L"C:/Users/ziad.elmously/OneDrive - Metrixlab/Documents/R/R-4.0.5/bin/x64" -lR ;
rm -f tmp.def;
fi
fi
Error in inDL(x, as.logical(local), as.logical(now), …) :
unable to load shared object ‘C:/Users/ziad.elmously/AppData/Local/Temp/RtmpU9H5Xz/file3ae07613718e.dll’:
LoadLibrary failure: A dynamic link library (DLL) initialization routine failed.
In addition: Warning message:
In system(paste(CXX, ARGS), ignore.stdout = TRUE, ignore.stderr = TRUE) :
‘C:/rtools40/usr/mingw_/bin/g++’ not found

[andrjohns]

Can you try pausing your Onedrive syncing and then trying again?

[zelmously]

I finally got it to work. I installed latest version of R (4.1.1) for Windows and I re-installed the “rstan” package using the command below:

install.packages(“rstan”, type = “binary”, dependencies = TRUE, repos = “https://cloud.r-project.org”)

If I run into the same problem in the future, I will try the solution you suggested.

I very much appreciate your support.

Sincerely,

Ziad Elmously