التفاصيل البيبلوغرافية
| العنوان: |
On the Family of Covariance Functions Based on ARMA Models |
| المؤلفون: |
Till Schubert, Jan Martin Brockmann, Johannes Korte, Wolf-Dieter Schuh |
| المصدر: |
Engineering Proceedings; Volume 5; Issue 1; Pages: 37 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2021 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
ARMA processes, covariance function, stochastic modeling, time series analysis, Matérn covariance function, positive definiteness |
| الوصف: |
In time series analyses, covariance modeling is an essential part of stochastic methods such as prediction or filtering. For practical use, general families of covariance functions with large flexibilities are necessary to model complex correlations structures such as negative correlations. Thus, families of covariance functions should be as versatile as possible by including a high variety of basis functions. Another drawback of some common covariance models is that they can be parameterized in a way such that they do not allow all parameters to vary. In this work, we elaborate on the affiliation of several established covariance functions such as exponential, Matérn-type, and damped oscillating functions to the general class of covariance functions defined by autoregressive moving average (ARMA) processes. Furthermore, we present advanced limit cases that also belong to this class and enable a higher variability of the shape parameters and, consequently, the representable covariance functions. For prediction tasks in applications with spatial data, the covariance function must be positive semi-definite in the respective domain. We provide conditions for the shape parameters that need to be fulfilled for positive semi-definiteness of the covariance function in higher input dimensions. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
https://dx.doi.org/10.3390/engproc2021005037 |
| DOI: |
10.3390/engproc2021005037 |
| الاتاحة: |
https://doi.org/10.3390/engproc2021005037 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: |
edsbas.8AEFDCC8 |
| قاعدة البيانات: |
BASE |