quantspec-package: Quantile-Based Spectral Analysis of Time Series

Description

Methods to determine, smooth and plot quantile periodograms for univariate and (since v1.2-0) multivariate time series. See Kley (2016) <doi:10.18637/jss.v070.i03> for a description and tutorial.

Arguments

The quantspec package contains a hierachy of S4 classes with corresponding methods and functions serving as constructors. The following class diagrams provide an overview on the structure of the package. In the first and second class diagram the classes implementing the estimators are shown. In the first diagram the classes related to periodogram-based estimation are displayed:

In the second diagram the classes related to lag window-based estimation are displayed:

In the third class diagram the classes implementing model quantities are displayed. A relation to the ``empirical classes'' is given via the fact that the quantile spectral densities are computed by simulation of quantile periodograms and a common abstract superclass QSpecQuantity which is used to provide a common interface to quantile spectral quantities.

Besides the object-oriented design a few auxiliary functions exists. They serve as parameters or are mostly for internal use. A more detailed description of the framework can be found in the paper on the package (Kley, 2016).

Organization of the source code / files in the <code>/R</code> folder

All of the source code related to the specification of a certain class is contained in a file named Class-[Name_of_the_class].R. This includes, in the following order,

all roxygen @include to insure the correctly generated collate for the DESCRIPTION file.
\setClass preceded by a meaningful roxygen documentation.
specification of an initialize method, where appropriate.
all accessor and mutator method (i. e., getter and setter); first the ones returning attributes of the object, then the ones returning associated objects.
constructors; use generics if there is more than one of them.
show and plot methods.

Coding Conventions

To improve readability of the software and documentation this package was written in the spirit of the ``Coding conventions of the Java Programming Language'' (Oracle, 2015). In particular, the naming conventions for classes and methods have been adopted, where ``Class names should be nouns, in mixed case with the first letter of each internal word capitalized.'' and ``Methods should be verbs, in mixed case with the first letter lowercase, with the first letter of each internal word capitalized.''

Naming Conventions for the Documentation

To reflect the structure of the contents of the package in the documentation file, the following system for naming of the sections is adopted:

Documentation of an S4 class is named as the name of the class followed by ``-class''. [cf. QuantilePG-class]
Documentation of a constructor for an S4-class is named as the name of the class followed by ``-constructor''. [cf. QuantilePG-constructor]
Documentation of a method dispaching to an object of a certain S4 class is named by the name of the method, followed by ``-'', followed by the name of the Class. [cf. getValues-QuantilePG]

Author

Tobias Kley

Details

	Package:
quantspec	Type:
Package	Version:
1.2-4	Date:
2024-07-10	License:

References

Kley, T. (2014a). Quantile-Based Spectral Analysis: Asymptotic Theory and Computation. Ph.D. Dissertation, Ruhr University Bochum. https://hss-opus.ub.ruhr-uni-bochum.de/opus4/frontdoor/index/index/docId/3894.

Kley, T. (2016). Quantile-Based Spectral Analysis in an Object-Oriented Framework and a Reference Implementation in R: The quantspec Package. Journal of Statistical Software, 70(3), 1--27.

Dette, H., Hallin, M., Kley, T. & Volgushev, S. (2015). Of Copulas, Quantiles, Ranks and Spectra: an \(L_1\)-approach to spectral analysis. Bernoulli, 21(2), 781--831. [cf. http://arxiv.org/abs/1111.7205]

Kley, T., Volgushev, S., Dette, H. & Hallin, M. (2016). Quantile Spectral Processes: Asymptotic Analysis and Inference. Bernoulli, 22(3), 1770--1807. [cf. http://arxiv.org/abs/1401.8104]

Barunik, J. & Kley, T. (2019). Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables. Econometrics Journal, 22, 131--152. [cf. http://arxiv.org/abs/1510.06946]

Oracle (2015). Coding conventions of the Java Programming Language. https://www.oracle.com/java/technologies/javase/codeconventions-contents.html. Accessed 2015-03-25.