| canStopEM() | PLearn::RandomVariable | [virtual] |
| classname() | PLearn::DiagonalNormalRandomVariable | [inline, virtual] |
| clearEMmarks() | PLearn::RandomVariable | [virtual] |
| denom | PLearn::DiagonalNormalRandomVariable | [protected] |
| DiagonalNormalRandomVariable(const RandomVar &mean, const RandomVar &log_variance, real minimum_standard_deviation=1e-10) | PLearn::DiagonalNormalRandomVariable | |
| ElogP(const Var &obs, RVArray ¶meters_to_learn, const RVInstanceArray &RHS) | PLearn::RandomVariable | [virtual] |
| EM(const RVArray ¶meters_to_learn, VarArray &prop_path, VarArray &observedVars, VMat distr, int n_samples, int max_n_iterations, real relative_improvement_threshold, bool accept_worsening_likelihood=false) | PLearn::RandomVariable | [virtual] |
| EMBprop(const Vec obs, real posterior) | PLearn::DiagonalNormalRandomVariable | [virtual] |
| EMEpochInitialize() | PLearn::DiagonalNormalRandomVariable | [virtual] |
| EMmark | PLearn::RandomVariable | [protected] |
| EMTrainingInitialize(const RVArray ¶meters_to_learn) | PLearn::RandomVariable | [virtual] |
| EMUpdate() | PLearn::DiagonalNormalRandomVariable | [virtual] |
| epoch(VarArray &prop_path, VarArray &observed_vars, const VMat &distr, int n_samples, bool do_EM_learning=true) | PLearn::RandomVariable | [virtual] |
| isColumnVec() | PLearn::RandomVariable | [inline] |
| isConstant() | PLearn::RandomVariable | [inline] |
| isDiscrete() | PLearn::StochasticRandomVariable | [inline, virtual] |
| isMarked() | PLearn::RandomVariable | [inline, virtual] |
| isNonRandom() | PLearn::StochasticRandomVariable | [inline, virtual] |
| isRowVec() | PLearn::RandomVariable | [inline] |
| isScalar() | PLearn::RandomVariable | [inline] |
| isVec() | PLearn::RandomVariable | [inline] |
| learn_the_mean() | PLearn::DiagonalNormalRandomVariable | [inline] |
| learn_the_parameters | PLearn::RandomVariable | [protected] |
| learn_the_variance() | PLearn::DiagonalNormalRandomVariable | [inline] |
| length() | PLearn::RandomVariable | [inline, virtual] |
| log_variance() | PLearn::DiagonalNormalRandomVariable | [inline] |
| logP(const Var &obs, const RVInstanceArray &RHS, RVInstanceArray *parameters_to_learn) | PLearn::DiagonalNormalRandomVariable | [virtual] |
| mark(Var v) | PLearn::RandomVariable | [inline, virtual] |
| mark() | PLearn::RandomVariable | [inline, virtual] |
| marked | PLearn::RandomVariable | [protected] |
| markRHSandSetKnownValues(const RVInstanceArray &RHS) | PLearn::RandomVariable | [inline] |
| mean() | PLearn::DiagonalNormalRandomVariable | [inline] |
| minimum_variance | PLearn::DiagonalNormalRandomVariable | [protected] |
| mu_num | PLearn::DiagonalNormalRandomVariable | [protected] |
| nelems() | PLearn::RandomVariable | [inline] |
| normfactor | PLearn::DiagonalNormalRandomVariable | [protected] |
| P(const Var &obs, const RVInstanceArray &RHS) | PLearn::RandomVariable | [virtual] |
| parents | PLearn::RandomVariable | |
| pmark | PLearn::RandomVariable | [protected] |
| PPointable() | PLearn::PPointable | [inline] |
| PPointable(const PPointable &other) | PLearn::PPointable | [inline] |
| RandomVariable(int thelength, int thewidth=1) | PLearn::RandomVariable | |
| RandomVariable(const Vec &the_value) | PLearn::RandomVariable | |
| RandomVariable(const Mat &the_value) | PLearn::RandomVariable | |
| RandomVariable(const Var &the_value) | PLearn::RandomVariable | |
| RandomVariable(const RVArray &parents, int thelength) | PLearn::RandomVariable | |
| RandomVariable(const RVArray &parents, int thelength, int thewidth) | PLearn::RandomVariable | |
| ref() const | PLearn::PPointable | [inline] |
| rv_number | PLearn::RandomVariable | [protected] |
| setKnownValues() | PLearn::StochasticRandomVariable | [virtual] |
| setValueFromParentsValue() | PLearn::DiagonalNormalRandomVariable | [virtual] |
| shared_variance | PLearn::DiagonalNormalRandomVariable | [protected] |
| sigma_num | PLearn::DiagonalNormalRandomVariable | [protected] |
| StochasticRandomVariable(int length=1) | PLearn::StochasticRandomVariable | |
| StochasticRandomVariable(const RVArray ¶ms, int length) | PLearn::StochasticRandomVariable | |
| StochasticRandomVariable(const RVArray ¶ms, int length, int width) | PLearn::StochasticRandomVariable | |
| subVec(int start, int length) | PLearn::RandomVariable | |
| unmark() | PLearn::RandomVariable | [inline, virtual] |
| unmarkAncestors() | PLearn::RandomVariable | [virtual] |
| unref() const | PLearn::PPointable | [inline] |
| usage() const | PLearn::PPointable | [inline] |
| value | PLearn::RandomVariable | |
| width() | PLearn::RandomVariable | [inline, virtual] |
| ~PPointable() | PLearn::PPointable | [inline, virtual] |
| ~RandomVariable() | PLearn::RandomVariable | [virtual] |
