| /dports/math/apache-commons-math/commons-math3-3.6.1-src/src/test/java/org/apache/commons/math3/analysis/function/ |
| H A D | LogitTest.java | 73 final Logit f = new Logit(lo, hi); in testDerivative()
81 final Logit f = new Logit(1, 2); in testDerivativeLargeArguments()
110 final Logit.Parametric g = new Logit.Parametric(); in testParametricUsage1()
116 final Logit.Parametric g = new Logit.Parametric(); in testParametricUsage2()
122 final Logit.Parametric g = new Logit.Parametric(); in testParametricUsage3()
128 final Logit.Parametric g = new Logit.Parametric(); in testParametricUsage4()
134 final Logit.Parametric g = new Logit.Parametric(); in testParametricUsage5()
140 final Logit.Parametric g = new Logit.Parametric(); in testParametricUsage6()
148 final Logit f = new Logit(lo, hi); in testParametricValue()
160 final Logit f = new Logit(lo, hi); in testValueWithInverseFunction()
[all …]
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| /dports/benchmarks/postal/postal-0.73/ |
| H A D | logit.h | 10 class Logit
13 Logit(const char *filename, bool is_verbose, bool numbered_files, int pid);
14 ~Logit();
21 Logit(const Logit &l, int pid);
30 Logit(const Logit&);
31 Logit & operator=(const Logit&);
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| H A D | logit.cpp | 5 Logit::Logit(const char *filename, bool is_verbose, bool numbered_files, int pid) in Logit() function in Logit
15 Logit::Logit(const Logit &l, int pid) in Logit() function in Logit
25 bool Logit::reopen() in reopen()
61 Logit::~Logit() in ~Logit()
70 int Logit::Write(const char *data, size_t len) in Write()
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| H A D | basictcp.h | 12 class Logit; variable
39 base_tcp(int fd, Logit *log, Logit *debug, results *res
82 Logit *m_log;
86 Logit *m_debug;
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| H A D | tcp.h | 16 class Logit; variable
41 tcp(int *exitCount, const char *addr, unsigned short default_port, Logit *log
45 , const char *sourceAddr, Logit *debug);
79 Logit *m_log;
99 Logit *m_debug;
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| H A D | rabid.cpp | 165 Logit log("rabid.log", logAll, false, 0); in main()
166 Logit *debug = NULL; in main()
169 debug = new Logit(debugName, false, debugMultipleFiles, 0); in main()
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| H A D | bhm.cpp | 48 Logit *bhm_log;
65 Logit *debug;
409 bhm_log = new Logit("bhm.log", allLog, false, 0); in main()
410 Logit *debug = NULL; in main()
413 debug = new Logit(debugName, false, debugMultipleFiles, 0); in main()
483 td->debug = debug ? new Logit(*debug, i) : NULL; in main()
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| H A D | postal.cpp | 179 Logit log("postal.log", allLog, false, 0); in main()
180 Logit *debug = NULL; in main()
183 debug = new Logit(debugName, false, debugMultipleFiles, 0); in main()
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| H A D | smtpserver.h | 16 , int processes, Logit *log, Logit *debug
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| H A D | client.h | 15 , int processes, int msgsPerConnection, Logit *log
20 , Logit *debug);
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| H A D | smtpserver.cpp | 9 , int processes, Logit *log, Logit *debug in smtp_server()
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| H A D | smtp.h | 94 , int numMsgsPerConnection, int processes, Logit *log, TRISTATE netscape
99 , unsigned short port, Logit *debug);
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| /dports/math/jags/JAGS-4.3.0/src/modules/bugs/functions/ |
| H A D | Logit.cc | 12 Logit::Logit ():ScalarFunction ("logit", 1) in Logit() function in jags::bugs::Logit
16 double Logit::evaluate(vector <double const *> const &args) const in evaluate()
22 bool Logit::checkParameterValue (vector <double const *> const &args) const in checkParameterValue()
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| H A D | Logit.h | 17 class Logit:public ScalarFunction
20 Logit();
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| H A D | Makefile.am | 11 Exp.cc LogFact.cc LogGam.cc Phi.cc Logit.cc Inverse.cc LogDet.cc \
18 noinst_HEADERS = LogGam.h Phi.h Sum.h Log.h Logit.h Probit.h \
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| /dports/math/apache-commons-math/commons-math3-3.6.1-src/src/main/java/org/apache/commons/math3/analysis/function/ |
| H A D | Logit.java | 38 public class Logit implements UnivariateDifferentiableFunction, DifferentiableUnivariateFunction { class
48 public Logit() { in Logit() method in Logit
58 public Logit(double lo, in Logit() method in Logit
101 return Logit.value(x, param[0], param[1]); in value()
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| /dports/math/py-statsmodels/statsmodels-0.13.1/docs/source/ |
| H A D | discretemod.rst | 10 currently allows the estimation of models with binary (Logit, Probit), nominal
31 # Logit Model
32 logit_mod = sm.Logit(spector_data.endog, spector_data.exog)
78 Logit
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| /dports/math/py-spglm/spglm-1.0.8/spglm/ |
| H A D | links.py | 99 class Logit(Link): class
232 class logit(Logit):
541 class CDFLink(Logit):
696 class CLogLog(Logit):
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| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/genmod/families/ |
| H A D | links.py | 118 class Logit(Link): class
249 class logit(Logit):
590 class CDFLink(Logit):
806 class CLogLog(Logit):
931 class LogLog(Logit):
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| /dports/science/R-cran-bayesm/bayesm/man/ |
| H A D | mnlHess.Rd | 7 \title{ Computes --Expected Hessian for Multinomial Logit}
9 \description{\code{mnlHess} computes expected Hessian (\eqn{E[H]}) for Multinomial Logit Model.}
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| /dports/math/py-statsmodels/statsmodels-0.13.1/examples/notebooks/ |
| H A D | ordinal_regression.ipynb | 136 "### Logit ordinal regression:"
468 "### Binary Model compared to Logit\n",
470 … dependent ordered categorical variable, then the model can also be estimated by a Logit model.\n",
472 …) identical in this case except for the parameterization of the constant. Logit as most other mode…
483 "from statsmodels.discrete.discrete_model import Logit\n",
525 …"The Logit model does not have a constant by default, we have to add it to our explanatory variabl…
527 …"The results are essentially identical between Logit and ordered model up to numerical precision m…
529 …"The only difference is in the sign of the constant, Logit and OrdereModel have opposite signs of …
539 "mod_logit = Logit(data2['apply'].cat.codes, ex)\n",
557 …"Robust standard errors are also available in OrderedModel in the same way as in discrete.Logit.\n…
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| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/genmod/families/tests/ |
| H A D | test_family.py | 10 L.Logit, L.logit, L.Power, L.inverse_power, L.sqrt, L.inverse_squared,
18 L.Logit, L.logit, L.probit, L.cauchy, L.Log, L.log, L.CLogLog,
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| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/examples/l1_demo/ |
| H A D | short_demo.py | 32 logit_mod = sm.Logit(spector_data.endog, spector_data.exog)
91 logit_mod = sm.Logit(Y, X)
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| /dports/science/R-cran-bayesm/bayesm/ |
| H A D | DESCRIPTION | 21 Multinomial Logit (MNL) and Multinomial Probit (MNP),
36 Bayesian Analysis of Aggregate Random Coefficient Logit Models as in BLP (see
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| /dports/math/apache-commons-math/commons-math3-3.6.1-src/src/main/java/org/apache/commons/math3/optim/nonlinear/scalar/ |
| H A D | MultivariateFunctionMappingAdapter.java | 21 import org.apache.commons.math3.analysis.function.Logit;
281 unboundingFunction = new Logit(lower, upper); in LowerUpperBoundMapper()
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