Hello.
I intend to adjust the models in Stan. However, compilation errors have occurred. For example:
Error in compileCode(f, code, language = language, verbose = verbose) :
from file2e31e1a11c3.cpp:8:/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/BH/include/boost/throw_exception.hpp: In function ‘void boost::throw_exception(const E&)’:/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/BH/include/boost/throw_exception.hpp:70:11: error: ‘enable_both’ is not a member of ‘boost::exception_detail’ throw exception_detail::enable_both( e ); ^make: *** [file2e31e1a11c3.o] Error 1
Calls: Ajuste_alfa … stan_model -> cxxfunctionplus -> cxxfunction -> compileCode
It also gives me the output type:
ERROR(s) during compilation: source code errors or compiler configuration errors!
make cmd is
make -f ‘/mnt/nfs/modules/apps/R/3.3.3/lib64/R/etc/Makeconf’ -f ‘/mnt/nfs/modules/apps/R/3.3.3/lib64/R/share/make/shlib.mk’ -f ‘/home/fabiano_coelho/.R/Makevars’ SHLIB_LDFLAGS=’(SHLIB_CXXLDFLAGS)' SHLIB_LD='(SHLIB_CXXLD)’ SHLIB=‘file2e31e1a11c3.so’ OBJECTS=‘file2e31e1a11c3.o’
make would use
g++ -I/mnt/nfs/modules/apps/R/3.3.3/lib64/R/include -DNDEBUG -I"/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/Rcpp/include/" -I"/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/RcppEigen/include/" -I"/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/RcppEigen/include/unsupported" -I"/mnt/nfs/modules/apps/R/3.3.3/lib64/R/library/rstan/include/boost_not_in_BH" -I"/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/BH/include" -I"/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/StanHeaders/include/src/" -I"/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/StanHeaders/include/" -I"/mnt/nfs/modules/apps/R/3.3.3/lib64/R/library/rstan/include" -DEIGEN_NO_DEBUG -DBOOST_RESULT_OF_USE_TR1 -DBOOST_NO_DECLTYPE -DBOOST_DISABLE_ASSERTS -DBOOST_NO_CXX11_RVALUE_REFERENCES -I/usr/local/include -fpic -g -O2 -c file2e31e1a11c3.cpp -o file2e31e1a11c3.o
if test “zfile2e31e1a11c3.o” != “z”; then
echo g++ -shared -L/usr/local/lib64 -o file2e31e1a11c3.so file2e31e1a11c3.o -L’/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/StanHeaders/lib’ -lStanHeaders ;
g++ -shared -L/usr/local/lib64 -o file2e31e1a11c3.so file2e31e1a11c3.o -L’/mnt/nfs/home/fabiano_coelho/R/x86_64-pc-linux-gnu-library/3.3/StanHeaders/lib’ -lStanHeaders ;
fi
Program source:
1:
2: // includes from the plugin
3:
4:
5: // user includes
6: #define STAN__SERVICES__COMMAND_HPP// Code generated by Stan version 2.15.0
7:
8: #include <stan/model/model_header.hpp>
9:
10: namespace model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace {
11:
12: using std::istream;
13: using std::string;
14: using std::stringstream;
15: using std::vector;
16: using stan::io::dump;
17: using stan::math::lgamma;
18: using stan::model::prob_grad;
19: using namespace stan::math;
20:
21: typedef Eigen::Matrix<double,Eigen::Dynamic,1> vector_d;
22: typedef Eigen::Matrix<double,1,Eigen::Dynamic> row_vector_d;
23: typedef Eigen::Matrix<double,Eigen::Dynamic,Eigen::Dynamic> matrix_d;
24:
25: static int current_statement_begin__;
26:
27: class model2e317d063a50_b695adad213ef10eb00d858f049c77a2 : public prob_grad {
28: private:
29: int N;
30: vector y;
31: vector X;
32: public:
33: model2e317d063a50_b695adad213ef10eb00d858f049c77a2(stan::io::var_context& context__,
34: std::ostream* pstream__ = 0)
35: : prob_grad(0) {
36: typedef boost::ecuyer1988 rng_t;
37: rng_t base_rng(0); // 0 seed default
38: ctor_body(context__, base_rng, pstream__);
39: }
40:
41: template
42: model2e317d063a50_b695adad213ef10eb00d858f049c77a2(stan::io::var_context& context__,
43: RNG& base_rng__,
44: std::ostream* pstream__ = 0)
45: : prob_grad(0) {
46: ctor_body(context__, base_rng__, pstream__);
47: }
48:
49: template
50: void ctor_body(stan::io::var_context& context__,
51: RNG& base_rng__,
52: std::ostream* pstream__) {
53: current_statement_begin__ = -1;
54:
55: static const char* function__ = “model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2”;
56: (void) function__; // dummy to suppress unused var warning
57: size_t pos__;
58: (void) pos__; // dummy to suppress unused var warning
59: std::vector vals_i__;
60: std::vector vals_r__;
61: double DUMMY_VAR__(std::numeric_limits::quiet_NaN());
62: (void) DUMMY_VAR__; // suppress unused var warning
63:
64: // initialize member variables
65: context__.validate_dims(“data initialization”, “N”, “int”, context__.to_vec());
66: N = int(0);
67: vals_i__ = context__.vals_i(“N”);
68: pos__ = 0;
69: N = vals_i__[pos__++];
70: validate_non_negative_index(“y”, “N”, N);
71: context__.validate_dims(“data initialization”, “y”, “int”, context__.to_vec(N));
72: validate_non_negative_index(“y”, “N”, N);
73: y = std::vector(N,int(0));
74: vals_i__ = context__.vals_i(“y”);
75: pos__ = 0;
76: size_t y_limit_0__ = N;
77: for (size_t i_0__ = 0; i_0__ < y_limit_0__; ++i_0__) {
78: y[i_0__] = vals_i__[pos__++];
79: }
80: validate_non_negative_index(“X”, “N”, N);
81: context__.validate_dims(“data initialization”, “X”, “double”, context__.to_vec(N));
82: validate_non_negative_index(“X”, “N”, N);
83: X = std::vector(N,double(0));
84: vals_r__ = context__.vals_r(“X”);
85: pos__ = 0;
86: size_t X_limit_0__ = N;
87: for (size_t i_0__ = 0; i_0__ < X_limit_0__; ++i_0__) {
88: X[i_0__] = vals_r__[pos__++];
89: }
90:
91: // validate, data variables
92: check_greater_or_equal(function__,“N”,N,1);
93: for (int k0__ = 0; k0__ < N; ++k0__) {
94: check_greater_or_equal(function__,“y[k0__]”,y[k0__],0);
95: check_less_or_equal(function__,“y[k0__]”,y[k0__],1);
96: }
97: // initialize data variables
98:
99: try {
100: } catch (const std::exception& e) {
101: stan::lang::rethrow_located(e,current_statement_begin__);
102: // Next line prevents compiler griping about no return
103: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ");
104: }
105:
106: // validate transformed data
107:
108: // validate, set parameter ranges
109: num_params_r__ = 0U;
110: param_ranges_i__.clear();
111: ++num_params_r__;
112: ++num_params_r__;
113: ++num_params_r__;
114: }
115:
116: ~model2e317d063a50_b695adad213ef10eb00d858f049c77a2() { }
117:
118:
119: void transform_inits(const stan::io::var_context& context__,
120: std::vector& params_i__,
121: std::vector& params_r__,
122: std::ostream pstream__) const {
123: stan::io::writer writer__(params_r__,params_i__);
124: size_t pos__;
125: (void) pos__; // dummy call to supress warning
126: std::vector vals_r__;
127: std::vector vals_i__;
128:
129: if (!(context__.contains_r(“beta”)))
130: throw std::runtime_error(“variable beta missing”);
131: vals_r__ = context__.vals_r(“beta”);
132: pos__ = 0U;
133: context__.validate_dims(“initialization”, “beta”, “double”, context__.to_vec());
134: // generate_declaration beta
135: double beta(0);
136: beta = vals_r__[pos__++];
137: try {
138: writer__.scalar_unconstrain(beta);
139: } catch (const std::exception& e) {
140: throw std::runtime_error(std::string("Error transforming variable beta: ") + e.what());
141: }
142:
143: if (!(context__.contains_r(“beta0”)))
144: throw std::runtime_error(“variable beta0 missing”);
145: vals_r__ = context__.vals_r(“beta0”);
146: pos__ = 0U;
147: context__.validate_dims(“initialization”, “beta0”, “double”, context__.to_vec());
148: // generate_declaration beta0
149: double beta0(0);
150: beta0 = vals_r__[pos__++];
151: try {
152: writer__.scalar_unconstrain(beta0);
153: } catch (const std::exception& e) {
154: throw std::runtime_error(std::string("Error transforming variable beta0: ") + e.what());
155: }
156:
157: if (!(context__.contains_r(“alfa”)))
158: throw std::runtime_error(“variable alfa missing”);
159: vals_r__ = context__.vals_r(“alfa”);
160: pos__ = 0U;
161: context__.validate_dims(“initialization”, “alfa”, “double”, context__.to_vec());
162: // generate_declaration alfa
163: double alfa(0);
164: alfa = vals_r__[pos__++];
165: try {
166: writer__.scalar_unconstrain(alfa);
167: } catch (const std::exception& e) {
168: throw std::runtime_error(std::string("Error transforming variable alfa: ") + e.what());
169: }
170:
171: params_r__ = writer__.data_r();
172: params_i__ = writer__.data_i();
173: }
174:
175: void transform_inits(const stan::io::var_context& context,
176: Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
177: std::ostream pstream__) const {
178: std::vector params_r_vec;
179: std::vector params_i_vec;
180: transform_inits(context, params_i_vec, params_r_vec, pstream__);
181: params_r.resize(params_r_vec.size());
182: for (int i = 0; i < params_r.size(); ++i)
183: params_r(i) = params_r_vec[i];
184: }
185:
186:
187: template <bool propto__, bool jacobian__, typename T__>
188: T__ log_prob(vector<T__>& params_r__,
189: vector& params_i__,
190: std::ostream pstream__ = 0) const {
191:
192: T__ DUMMY_VAR__(std::numeric_limits::quiet_NaN());
193: (void) DUMMY_VAR__; // suppress unused var warning
194:
195: T__ lp__(0.0);
196: stan::math::accumulator<T__> lp_accum__;
197:
198: // model parameters
199: stan::io::reader<T__> in__(params_r__,params_i__);
200:
201: T__ beta;
202: (void) beta; // dummy to suppress unused var warning
203: if (jacobian__)
204: beta = in__.scalar_constrain(lp__);
205: else
206: beta = in__.scalar_constrain();
207:
208: T__ beta0;
209: (void) beta0; // dummy to suppress unused var warning
210: if (jacobian__)
211: beta0 = in__.scalar_constrain(lp__);
212: else
213: beta0 = in__.scalar_constrain();
214:
215: T__ alfa;
216: (void) alfa; // dummy to suppress unused var warning
217: if (jacobian__)
218: alfa = in__.scalar_constrain(lp__);
219: else
220: alfa = in__.scalar_constrain();
221:
222:
223: // transformed parameters
224: T__ delta;
225: (void) delta; // dummy to suppress unused var warning
226:
227: stan::math::initialize(delta, DUMMY_VAR__);
228: stan::math::fill(delta,DUMMY_VAR__);
229: validate_non_negative_index(“prob”, “N”, N);
230: Eigen::Matrix<T__,Eigen::Dynamic,1> prob(static_castEigen::VectorXd::Index(N));
231: (void) prob; // dummy to suppress unused var warning
232:
233: stan::math::initialize(prob, DUMMY_VAR__);
234: stan::math::fill(prob,DUMMY_VAR__);
235: validate_non_negative_index(“mu”, “N”, N);
236: Eigen::Matrix<T__,Eigen::Dynamic,1> mu(static_castEigen::VectorXd::Index(N));
237: (void) mu; // dummy to suppress unused var warning
238:
239: stan::math::initialize(mu, DUMMY_VAR__);
240: stan::math::fill(mu,DUMMY_VAR__);
241:
242:
243: try {
244: current_statement_begin__ = 16;
245: stan::math::assign(delta, (alfa / sqrt((1 + pow(alfa,2)))));
246: current_statement_begin__ = 17;
247: for (int i = 1; i <= N; ++i) {
248:
249: current_statement_begin__ = 18;
250: stan::math::assign(get_base1_lhs(mu,i,“mu”,1), (beta0 + (beta * get_base1(X,i,“X”,1))));
251: current_statement_begin__ = 19;
252: stan::math::assign(get_base1_lhs(prob,i,“prob”,1), skew_normal_cdf(get_base1(mu,i,“mu”,1),((-(sqrt(2)) * alfa) / sqrt((stan::math::pi() + ((stan::math::pi() - 2) * pow(alfa,2))))),((stan::math::pi() + (stan::math::pi() * pow(alfa,2))) / (stan::math::pi() + ((stan::math::pi() - 2) * pow(alfa,2)))),alfa));
253: }
254: } catch (const std::exception& e) {
255: stan::lang::rethrow_located(e,current_statement_begin__);
256: // Next line prevents compiler griping about no return
257: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ");
258: }
259:
260: // validate transformed parameters
261: if (stan::math::is_uninitialized(delta)) {
262: std::stringstream msg__;
263: msg__ << “Undefined transformed parameter: delta”;
264: throw std::runtime_error(msg__.str());
265: }
266: for (int i0__ = 0; i0__ < N; ++i0__) {
267: if (stan::math::is_uninitialized(prob(i0__))) {
268: std::stringstream msg__;
269: msg__ << “Undefined transformed parameter: prob” << ‘[’ << i0__ << ‘]’;
270: throw std::runtime_error(msg__.str());
271: }
272: }
273: for (int i0__ = 0; i0__ < N; ++i0__) {
274: if (stan::math::is_uninitialized(mu(i0__))) {
275: std::stringstream msg__;
276: msg__ << “Undefined transformed parameter: mu” << ‘[’ << i0__ << ‘]’;
277: throw std::runtime_error(msg__.str());
278: }
279: }
280:
281: const char function__ = “validate transformed params”;
282: (void) function__; // dummy to suppress unused var warning
283:
284: // model body
285: try {
286:
287: current_statement_begin__ = 23;
288: lp_accum__.add(normal_log<propto__>(beta0, 0, 100));
289: current_statement_begin__ = 24;
290: lp_accum__.add(normal_log<propto__>(beta, 0, 100));
291: current_statement_begin__ = 25;
292: lp_accum__.add(normal_log<propto__>(alfa, 0, 2));
293: current_statement_begin__ = 26;
294: for (int i = 1; i <= N; ++i) {
295:
296: current_statement_begin__ = 27;
297: lp_accum__.add(bernoulli_log<propto__>(get_base1(y,i,“y”,1), get_base1(prob,i,“prob”,1)));
298: }
299: } catch (const std::exception& e) {
300: stan::lang::rethrow_located(e,current_statement_begin__);
301: // Next line prevents compiler griping about no return
302: throw std::runtime_error("* IF YOU SEE THIS, PLEASE REPORT A BUG ");
303: }
304:
305: lp_accum__.add(lp__);
306: return lp_accum__.sum();
307:
308: } // log_prob()
309:
310: template <bool propto, bool jacobian, typename T_>
311: T_ log_prob(Eigen::Matrix<T_,Eigen::Dynamic,1>& params_r,
312: std::ostream pstream = 0) const {
313: std::vector<T_> vec_params_r;
314: vec_params_r.reserve(params_r.size());
315: for (int i = 0; i < params_r.size(); ++i)
316: vec_params_r.push_back(params_r(i));
317: std::vector vec_params_i;
318: return log_prob<propto,jacobian,T_>(vec_params_r, vec_params_i, pstream);
319: }
320:
321:
322: void get_param_names(std::vectorstd::string& names__) const {
323: names__.resize(0);
324: names__.push_back(“beta”);
325: names__.push_back(“beta0”);
326: names__.push_back(“alfa”);
327: names__.push_back(“delta”);
328: names__.push_back(“prob”);
329: names__.push_back(“mu”);
330: }
331:
332:
333: void get_dims(std::vector<std::vector<size_t> >& dimss__) const {
334: dimss__.resize(0);
335: std::vector<size_t> dims__;
336: dims__.resize(0);
337: dimss__.push_back(dims__);
338: dims__.resize(0);
339: dimss__.push_back(dims__);
340: dims__.resize(0);
341: dimss__.push_back(dims__);
342: dims__.resize(0);
343: dimss__.push_back(dims__);
344: dims__.resize(0);
345: dims__.push_back(N);
346: dimss__.push_back(dims__);
347: dims__.resize(0);
348: dims__.push_back(N);
349: dimss__.push_back(dims__);
350: }
351:
352: template
353: void write_array(RNG& base_rng__,
354: std::vector& params_r__,
355: std::vector& params_i__,
356: std::vector& vars__,
357: bool include_tparams__ = true,
358: bool include_gqs__ = true,
359: std::ostream pstream__ = 0) const {
360: vars__.resize(0);
361: stan::io::reader in__(params_r__,params_i__);
362: static const char function__ = “model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::write_array”;
363: (void) function__; // dummy to suppress unused var warning
364: // read-transform, write parameters
365: double beta = in__.scalar_constrain();
366: double beta0 = in__.scalar_constrain();
367: double alfa = in__.scalar_constrain();
368: vars__.push_back(beta);
369: vars__.push_back(beta0);
370: vars__.push_back(alfa);
371:
372: if (!include_tparams__) return;
373: // declare and define transformed parameters
374: double lp__ = 0.0;
375: (void) lp__; // dummy to suppress unused var warning
376: stan::math::accumulator lp_accum__;
377:
378: double DUMMY_VAR__(std::numeric_limits::quiet_NaN());
379: (void) DUMMY_VAR__; // suppress unused var warning
380:
381: double delta(0.0);
382: (void) delta; // dummy to suppress unused var warning
383:
384: stan::math::initialize(delta, std::numeric_limits::quiet_NaN());
385: stan::math::fill(delta,DUMMY_VAR__);
386: validate_non_negative_index(“prob”, “N”, N);
387: vector_d prob(static_castEigen::VectorXd::Index(N));
388: (void) prob; // dummy to suppress unused var warning
389:
390: stan::math::initialize(prob, std::numeric_limits::quiet_NaN());
391: stan::math::fill(prob,DUMMY_VAR__);
392: validate_non_negative_index(“mu”, “N”, N);
393: vector_d mu(static_castEigen::VectorXd::Index(N));
394: (void) mu; // dummy to suppress unused var warning
395:
396: stan::math::initialize(mu, std::numeric_limits::quiet_NaN());
397: stan::math::fill(mu,DUMMY_VAR__);
398:
399:
400: try {
401: current_statement_begin__ = 16;
402: stan::math::assign(delta, (alfa / sqrt((1 + pow(alfa,2)))));
403: current_statement_begin__ = 17;
404: for (int i = 1; i <= N; ++i) {
405:
406: current_statement_begin__ = 18;
407: stan::math::assign(get_base1_lhs(mu,i,“mu”,1), (beta0 + (beta * get_base1(X,i,“X”,1))));
408: current_statement_begin__ = 19;
409: stan::math::assign(get_base1_lhs(prob,i,“prob”,1), skew_normal_cdf(get_base1(mu,i,“mu”,1),((-(sqrt(2)) * alfa) / sqrt((stan::math::pi() + ((stan::math::pi() - 2) * pow(alfa,2))))),((stan::math::pi() + (stan::math::pi() * pow(alfa,2))) / (stan::math::pi() + ((stan::math::pi() - 2) * pow(alfa,2)))),alfa));
410: }
411: } catch (const std::exception& e) {
412: stan::lang::rethrow_located(e,current_statement_begin__);
413: // Next line prevents compiler griping about no return
414: throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ");
415: }
416:
417: // validate transformed parameters
418:
419: // write transformed parameters
420: vars__.push_back(delta);
421: for (int k_0__ = 0; k_0__ < N; ++k_0__) {
422: vars__.push_back(prob[k_0__]);
423: }
424: for (int k_0__ = 0; k_0__ < N; ++k_0__) {
425: vars__.push_back(mu[k_0__]);
426: }
427:
428: if (!include_gqs__) return;
429: // declare and define generated quantities
430:
431:
432: try {
433: } catch (const std::exception& e) {
434: stan::lang::rethrow_located(e,current_statement_begin__);
435: // Next line prevents compiler griping about no return
436: throw std::runtime_error(" IF YOU SEE THIS, PLEASE REPORT A BUG ");
437: }
438:
439: // validate generated quantities
440:
441: // write generated quantities
442: }
443:
444: template
445: void write_array(RNG& base_rng,
446: Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
447: Eigen::Matrix<double,Eigen::Dynamic,1>& vars,
448: bool include_tparams = true,
449: bool include_gqs = true,
450: std::ostream pstream = 0) const {
451: std::vector params_r_vec(params_r.size());
452: for (int i = 0; i < params_r.size(); ++i)
453: params_r_vec[i] = params_r(i);
454: std::vector vars_vec;
455: std::vector params_i_vec;
456: write_array(base_rng,params_r_vec,params_i_vec,vars_vec,include_tparams,include_gqs,pstream);
457: vars.resize(vars_vec.size());
458: for (int i = 0; i < vars.size(); ++i)
459: vars(i) = vars_vec[i];
460: }
461:
462: static std::string model_name() {
463: return “model2e317d063a50_b695adad213ef10eb00d858f049c77a2”;
464: }
465:
466:
467: void constrained_param_names(std::vectorstd::string& param_names__,
468: bool include_tparams__ = true,
469: bool include_gqs__ = true) const {
470: std::stringstream param_name_stream__;
471: param_name_stream__.str(std::string());
472: param_name_stream__ << “beta”;
473: param_names__.push_back(param_name_stream__.str());
474: param_name_stream__.str(std::string());
475: param_name_stream__ << “beta0”;
476: param_names__.push_back(param_name_stream__.str());
477: param_name_stream__.str(std::string());
478: param_name_stream__ << “alfa”;
479: param_names__.push_back(param_name_stream__.str());
480:
481: if (!include_gqs__ && !include_tparams__) return;
482: param_name_stream__.str(std::string());
483: param_name_stream__ << “delta”;
484: param_names__.push_back(param_name_stream__.str());
485: for (int k_0__ = 1; k_0__ <= N; ++k_0__) {
486: param_name_stream__.str(std::string());
487: param_name_stream__ << “prob” << ‘.’ << k_0__;
488: param_names__.push_back(param_name_stream__.str());
489: }
490: for (int k_0__ = 1; k_0__ <= N; ++k_0__) {
491: param_name_stream__.str(std::string());
492: param_name_stream__ << “mu” << ‘.’ << k_0__;
493: param_names__.push_back(param_name_stream__.str());
494: }
495:
496: if (!include_gqs__) return;
497: }
498:
499:
500: void unconstrained_param_names(std::vectorstd::string& param_names__,
501: bool include_tparams__ = true,
502: bool include_gqs__ = true) const {
503: std::stringstream param_name_stream__;
504: param_name_stream__.str(std::string());
505: param_name_stream__ << “beta”;
506: param_names__.push_back(param_name_stream__.str());
507: param_name_stream__.str(std::string());
508: param_name_stream__ << “beta0”;
509: param_names__.push_back(param_name_stream__.str());
510: param_name_stream__.str(std::string());
511: param_name_stream__ << “alfa”;
512: param_names__.push_back(param_name_stream__.str());
513:
514: if (!include_gqs__ && !include_tparams__) return;
515: param_name_stream__.str(std::string());
516: param_name_stream__ << “delta”;
517: param_names__.push_back(param_name_stream__.str());
518: for (int k_0__ = 1; k_0__ <= N; ++k_0__) {
519: param_name_stream__.str(std::string());
520: param_name_stream__ << “prob” << ‘.’ << k_0__;
521: param_names__.push_back(param_name_stream__.str());
522: }
523: for (int k_0__ = 1; k_0__ <= N; ++k_0__) {
524: param_name_stream__.str(std::string());
525: param_name_stream__ << “mu” << ‘.’ << k_0__;
526: param_names__.push_back(param_name_stream__.str());
527: }
528:
529: if (!include_gqs__) return;
530: }
531:
532: }; // model
533:
534: }
535:
536: typedef model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2 stan_model;
537:
538: #include <rstan/rstaninc.hpp>
539: /
540: * Define Rcpp Module to expose stan_fit’s functions to R.
541: */
542: RCPP_MODULE(stan_fit4model2e317d063a50_b695adad213ef10eb00d858f049c77a2_mod){
543: Rcpp::class_<rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2,
544: boost::random::ecuyer1988> >(“stan_fit4model2e317d063a50_b695adad213ef10eb00d858f049c77a2”)
545: // .constructorRcpp::List()
546: .constructor<SEXP, SEXP>()
547: // .constructor<SEXP, SEXP>()
548: .method(“call_sampler”,
549: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::call_sampler)
550: .method(“param_names”,
551: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::param_names)
552: .method(“param_names_oi”,
553: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::param_names_oi)
554: .method(“param_fnames_oi”,
555: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::param_fnames_oi)
556: .method(“param_dims”,
557: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::param_dims)
558: .method(“param_dims_oi”,
559: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::param_dims_oi)
560: .method(“update_param_oi”,
561: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::update_param_oi)
562: .method(“param_oi_tidx”,
563: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::param_oi_tidx)
564: .method(“grad_log_prob”,
565: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::grad_log_prob)
566: .method(“log_prob”,
567: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::log_prob)
568: .method(“unconstrain_pars”,
569: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::unconstrain_pars)
570: .method(“constrain_pars”,
571: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::constrain_pars)
572: .method(“num_pars_unconstrained”,
573: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::num_pars_unconstrained)
574: .method(“unconstrained_param_names”,
575: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::unconstrained_param_names)
576: .method(“constrained_param_names”,
577: &rstan::stan_fit<model2e317d063a50_b695adad213ef10eb00d858f049c77a2_namespace::model2e317d063a50_b695adad213ef10eb00d858f049c77a2, boost::random::ecuyer1988>::constrained_param_names)
578: ;
579: }
580:
581: // declarations
582: extern “C” {
583: SEXP file2e31e1a11c3( ) ;
584: }
585:
586: // definition
587:
588: SEXP file2e31e1a11c3( ){
589: return Rcpp::wrap(“b695adad213ef10eb00d858f049c77a2”);
590: }
591:
592:
Compilation ERROR, function(s)/method(s) not created!
Timing stopped at: 56.799 2.749 60.053
Does anyone have any idea how to solve this?
I’m not using a personal computer, but a supercomputer (many grouped processors).
Gratefull