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FIMS
v0.8.1
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Base class for all module_name functors. More...
#include <density_components_base.hpp>
Public Member Functions | |
| Type & | get_observed (size_t i) |
Retrieve one observed value based on input_type. | |
| Type & | get_observed (size_t i, size_t j) |
Retrieve one observed matrix-like value based on input_type. | |
| Type & | get_expected (size_t i) |
Retrieve one expected value based on input_type and use_mean. | |
| size_t | get_n_x () |
| Get length of the active observed input vector. | |
| size_t | get_n_expected () |
| Get length of the active expected input vector. | |
| DensityComponentBase () | |
| Constructor, which initializes default prior pointer state and ID. | |
| virtual const Type | evaluate ()=0 |
| Evaluate the distribution-specific log-likelihood contribution. | |
Public Member Functions inherited from fims_model_object::FIMSObject< Type > | |
| uint32_t | GetId () const |
| Getter that returns the unique id for parameters in the model. | |
| bool | CheckDimensions (size_t actual, size_t expected) |
| Check the dimensions of an object. | |
Public Attributes | |
| std::string | input_type |
| Classification of the input pathway for this distribution object. Options used by accessor methods are, "prior", "random_effects", and "data". | |
| std::shared_ptr< fims_data_object::DataObject< Type > > | data_observed_values |
| Observed data. | |
| fims::Vector< Type > | expected_values |
| Expected value vector for prior-based pathways. | |
| fims::Vector< Type > * | re = NULL |
| Pointer to random effects vector. | |
| fims::Vector< Type > * | re_expected_values = NULL |
| Expected value vector for random-effects pathways. | |
| fims::Vector< Type > * | data_expected_values = NULL |
| Expected value vector for data pathways. | |
| std::vector< fims::Vector< Type > * > | priors |
| Vector of pointers where each entry points to a prior parameter. | |
| fims::Vector< Type > | observed_values |
| Input value of distribution function for priors or random effects. | |
| fims::Vector< Type > | expected_mean |
| The expected mean of the distribution; overrides expected values. | |
| std::string | use_mean = fims::to_string("no") |
If "yes", expected_mean is used instead of expected_values. The default is "no" leading to the use of expected_values. | |
| Type | lpdf |
| Total log probability density contribution of the distribution. | |
| int | observed_data_id_m = -999 |
| ID of observed data component. | |
| fims::Vector< Type > | lpdf_vec |
| Vector storing observation-level log-likelihood contributions. | |
| bool | osa_flag = false |
| Boolean; if true, one-step-ahead (OSA) residuals are calculated. | |
| bool | simulate_flag = false |
| Boolean; if true, data are simulated from the distribution. | |
| std::vector< uint32_t > | key |
| Unique ID for variable map that points to a fims::Vector. | |
Public Attributes inherited from fims_model_object::FIMSObject< Type > | |
| uint32_t | id |
| std::vector< Type * > | parameters |
| std::vector< Type * > | random_effects_parameters |
| std::vector< Type * > | fixed_effects_parameters |
Static Public Attributes | |
| static uint32_t | id_g = 0 |
| Global unique identifier for distribution modules. | |
Base class for all module_name functors.
| Type | The type of the module_name functor. |
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pure virtual |
Evaluate the distribution-specific log-likelihood contribution.
Implemented in fims_distributions::LogNormalLPDF< Type >, fims_distributions::MultinomialLPMF< Type >, and fims_distributions::NormalLPDF< Type >.
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inline |
Retrieve one expected value based on input_type and use_mean.
| i | Index into the active expected source, e.g., vector or pointer. |
If use_mean == "yes", expected_mean overrides other expected vectors and is accessed via scalar/vector semantics.
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inline |
Get length of the active expected input vector.
input_type.
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inline |
Get length of the active observed input vector.
input_type.
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inline |
Retrieve one observed value based on input_type.
| i | Index into the active observed source, e.g., vector or pointer. |
| std::runtime_error | If input_type is "prior" and priors is empty. |
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inline |
Retrieve one observed matrix-like value based on input_type.
| i | Row index. |
| j | Column index. |
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static |
Global unique identifier for distribution modules.
Default id of the singleton distribution class.