The mcmc_regression type extends the metropolis_hastings type to specifically target regression problems. The problem is formulated such that the target distribution takes the form , where is a normal distribution with as the mean and the model variance, is determined by computing the variance for the current estimate of the model.
| Type | Visibility | Attributes | Name | Initial | |||
|---|---|---|---|---|---|---|---|
| procedure(regression_function), | public, | pointer, nopass | :: | fcn |
The function to fit. |
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| real(kind=real64), | public, | allocatable, dimension(:) | :: | lower_limits |
An optional array that, if used, provides a lower limit to each parameter in the model. If used, be sure this array is the same dimension as the parameter array. If not used, leave this alone and no lower limits will be placed on the parameters. If used and the array is not sized correctly, it will be ignored. |
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| real(kind=real64), | public, | allocatable, dimension(:) | :: | upper_limits |
An optional array that, if used, provides an upper limit to each parameter in the model. If used, be sure this array is the same dimension as the parameter array. If not used, leave this alone and no upper limits will be placed on the parameters. If used and the array is not sized correctly, it will be ignored. |
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| real(kind=real64), | public, | allocatable, dimension(:) | :: | x |
The independent-variable data to fit. |
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| real(kind=real64), | public, | allocatable, dimension(:) | :: | y |
The dependent-variable data to fit. |
| procedure , public :: compute_fit_statistics => mr_calc_regression_stats Function | |
| procedure , public :: compute_hastings_ratio => mh_hastings_ratio Function | |
| procedure , public :: covariance_matrix => mr_covariance Function | |
| procedure , public :: evaluate_proposal_pdf => mh_eval_proposal Function | |
| procedure , public :: generate_proposal => mr_proposal Function | |
| procedure , public :: get_accepted_count => mh_get_num_accepted Function | |
| procedure , public :: get_chain => mh_get_chain Function | |
| procedure , public :: get_chain_length => mh_get_chain_length Function | |
| procedure , public :: get_data_variance => mr_get_data_variance Function | |
| procedure , public :: get_proposal_cholesky => mh_get_prop_chol_cov Function | |
| procedure , public :: get_proposal_covariance => mh_get_prop_cov Function | |
| procedure , public :: get_proposal_initialized => mh_get_is_prop_init Function | |
| procedure , public :: get_proposal_means => mh_get_prop_mean Function | |
| procedure , public :: get_state_variable_count => mh_get_nvars Function | |
| generic, public :: initialize_proposal => mh_init_proposal_1, mh_init_proposal_2 | |
| procedure , public :: likelihood => mr_likelihood Function | |
| procedure , public :: on_acceptance => mr_on_success Subroutine | |
| procedure , public :: on_rejection => mh_on_rejection Subroutine | |
| procedure , public :: push_new_state => mr_push Subroutine | |
| procedure , public :: reset => mh_clear_chain Subroutine | |
| procedure , public :: sample => mh_sample Subroutine | |
| procedure , public :: set_data_variance => mr_set_data_variance Subroutine | |
| procedure , public :: set_proposal_covariance => mh_set_prop_cov Subroutine | |
| procedure , public :: set_proposal_means => mh_set_prop_mean Subroutine | |
| procedure , public :: target_distribution => mr_target Function |