src Directory Reference

Files
	ADF_comp_pvalue_util.hpp
	Helper function and constant values to evaluate ADF-test p-value from the value of the statistic: how much the statistic has extreme negative values.
	ADF_comp_stat.hpp
	Implement the class to compute Augmented Dickey-Fuller (ADF) test statistic.
	ADF_lr.hpp
	Performing lineat regression.
	ADF_policies.hpp
	Implement the policies, through functors and template parameter, for considering or not bigger lag orders to perform pointwisely Augmented Dickey-Fuller (ADF) test on the fts.
	ADF_test.hpp
	Contains a class to perform pointwisely Augmented Dickey-Fuller (ADF) test on the fts.
	ADF_test_imp.hpp
	Implement the class to perform pointwisely Augmented Dickey-Fuller (ADF) test on the fts.
	CV.hpp
	Class for performing cross-validation.
	CV_alpha.hpp
	Derived-from-CV_base class for performing cross-validation on the regularization parameter alpha.
	CV_alpha_k.hpp
	Derived-from-CV_base class for performing cross-validation on both the regularization parameter and the number of retained PPCs.
	CV_err_valid_eval.hpp
	Implementation of tag-dispatched function for evaluating the validation error.
	cv_eval_valid_err.hpp
	Containing the definitions of the different ways of evaluating the validation error.
	CV_include.hpp
	CV_k.hpp
	Derived-from-CV_base class for performing cross-validation on the number of retained PPCs.
	data_reader.hpp
	Contains the method to read data.
	domain.cpp
	Class unidimensioanl domain definition.
	domain.hpp
	Contains the class for an unidimensioanl domain.
	Factory_cv_strategy.hpp
	Factory for generating the training-validation splitting according to the strategy given.
	Factory_ko.hpp
	Factory for generating the PPCKO solver.
	interp1D.hpp
	Contains the template class for interpolating an unidimensional-univariate function in a given point.
	interp1D_util.hpp
	Contains a specialization for the template class for interpolating an unidimensional-univariate function in a given point.
	interp_func.hpp
	Contains a functor to perform unidimensional-univariate function interpolation.
	mesh.cpp
	Contains the implementation of the class for an unidimensioanl mesh.
	mesh.hpp
	Contains the class for an unidimensioanl mesh.
	meshGenerators.cpp
	Contains implementation of the class for generating an unidimensional mesh. Little modification: retained only the part for an uniform mesh.
	meshGenerators.hpp
	Contains the class for generating an unidimensional mesh. Little modification: retained only the part for an uniform mesh.
	parameters_wrapper.hpp
	Contains methods to check and wrap R-inputs into PPCKO-coherent ones.
	PPC_KO.hpp
	Class for computing PPCKO algortihm. Hierarchy of classes, for different algorithm versions. Static polymorphism.
	PPC_KO_CV_alpha.hpp
	Class for computing PPCKO algortihm with cross-validation on the regularization parameter: k can be a parameter or selected through explanatory power criterion.
	PPC_KO_CV_alpha_k.hpp
	Class for computing PPCKO algortihm with cross-validation on both regularization parameter and number of retained PPCs.
	PPC_KO_CV_k.hpp
	Class for computing PPCKO algortihm with cross-validation on the number of retained PPCs: regularization parameter is a passed parameter.
	PPC_KO_imp.hpp
	Definition of methods of the base class for computing PPCKO.
	PPC_KO_include.hpp
	PPC_KO_NoCV.hpp
	Class for computing PPCKO algortihm without cross-validation: alpha as parameter, k can be a parameter or selected through explanatory power criterion.
	PPC_KO_Rinterface.cpp
	Contains the R-interfaced functions of the package 'PPCKO', which implement Principal Predictive Components (PPC) Kargin-Onatski (KO) algorithm to perform one-step ahead prediction of Functional Time Series (FTS).
	PPC_KO_wrapper.hpp
	Hierarchy of classes, for different algorithm versions. Correct child class is constructed by the KO_factory, providing the solver. Wrap the real class for computations.
	PPC_KO_wrapper_imp.hpp
	Implementation of the overriding of the virtual base method, depending on the child class.
	removing_nan.hpp
	Contains the class to remove (dummy and not dummy) NaNs.
	removing_nan_cleaner_imp.hpp
	Implementation of dummy NaNs removal.
	removing_nan_imp.hpp
	Implementation of non-dummy NaNs removal.
	strategy_cv.hpp
	Contains the class for creating the split training/validation set.
	strategy_cv_imp.hpp
	Definition of methods for creating training/validation splitting and recovering corresponding training/validation sets.
	traits_ko.hpp
	Contains customized types and enumerator for customized template parameters, exploited in the algorithm.
	utils.hpp
	Contains helpers functions.