vinecopulib::FitControlsBicop class

A class for controlling fits of bivariate copula models.

Derived classes

class FitControlsVinecop: A class for controlling fits of vine copula models.

FitControlsBicop(std::vector<BicopFamily> family_set = bicop_families::all, std::string parametric_method = "mle", std::string nonparametric_method = "quadratic", double nonparametric_mult = 1.0, std::string selection_criterion = "aic", const Eigen::VectorXd& weights = Eigen::VectorXd(), double psi0 = 0.9, bool preselect_families = true, size_t num_threads = 1): Instantiates the controls for fitting bivariate copula models.
FitControlsBicop(std::string parametric_method) explicit: Instantiates default controls except for the parameteric method.
FitControlsBicop(std::string nonparametric_method, double nonparametric_mult = 1.0) explicit: Instantiates default controls except for the nonparametric method.

auto str() const -> std::string: Summarizes the controls into a string (can be used for printing).

auto get_family_set() const -> std::vector<BicopFamily>: returns the family set.
auto get_parametric_method() const -> std::string: returns the parametric method.
auto get_nonparametric_method() const -> std::string: returns the nonparametric method.
auto get_nonparametric_mult() const -> double: returns the nonparametric bandwidth multiplier.
auto get_weights() const -> Eigen::VectorXd: returns the observation weights.
auto get_preselect_families() const -> bool: returns whether to preselect families.
auto get_psi0() const -> double: returns the baseline probability for mBIC selection.
auto get_num_threads() const -> size_t: returns the number of threads.
void set_family_set(std::vector<BicopFamily> family_set): Sets the family set.
void set_parametric_method(std::string parametric_method): Sets the parametric method.
void set_nonparametric_method(std::string nonparametric_method): Sets the nonparmetric method.
void set_nonparametric_mult(double nonparametric_mult): Sets the nonparametric multiplier.
void set_selection_criterion(std::string selection_criterion): Sets the selection criterion.
void set_weights(const Eigen::VectorXd& weights): Sets the observation weights.
void set_preselect_families(bool preselect_families): Sets whether to preselect the families.
void set_psi0(double psi0): Sets the prior probability for mBIC.
void set_num_threads(size_t num_threads): Sets the number of threads.

Instantiates the controls for fitting bivariate copula models.

Parameters
family_set	The set of copula families to consider (if empty, then all families are included).
parametric_method	The fit method for parametric families; possible choices: `"mle"`, `"itau"`.
nonparametric_method	The fit method for the local-likelihood nonparametric family (TLLs); possible choices: `"constant"`, `"linear"`, `"quadratic"`.
nonparametric_mult	A factor with which the smoothing parameters are multiplied.
selection_criterion	The selection criterion (`"loglik"`, `"aic"` or `"bic"`).
weights	A vector of weights for the observations.
psi0	Only for `selection_criterion = "mbic", the prior probability of non-independence.
preselect_families	Whether to exclude families before fitting based on symmetry properties of the data.
num_threads	Number of concurrent threads to use while fitting copulas for different families; never uses more than the number of concurrent threads supported by the implementation.

Instantiates default controls except for the parameteric method.

Parameters
parametric_method	The fit method for parametric families; possible choices: `"mle"`, `"itau"`.

Instantiates default controls except for the nonparametric method.

Parameters
nonparametric_method	The fit method for the local-likelihood nonparametric family (TLLs); possible choices: `"constant"`, `"linear"`, `"quadratic"`.
nonparametric_mult	A factor with which the smoothing parameters are multiplied.