Article Fingerprint
ReserarchID
5UNZ5
In many cases, it might be advisable to keep an operational time series model fixed for a given span of time, instead of updating it as a new datum becomes available. One common case, is represented by model-based deseasonalization procedures, whose time series models are updated on a regular basis by National Statistical Offices. In fact, in order to minimize the extent of the revisions and grant a greater stability of the already released figures, the interval in between two updating processes is kept “reasonably” long (e.g. one year). Other cases can be found in many contexts, e.g. in engineering for structural reliability analysis or in all those cases where model re-estimation is not a practical or even a viable options, e.g. due to time constraints or computational issues. Clearly, the inevitable trade-off between a fixed models and its updated counterpart, e.g. in terms of fitting performances, out-of-sample prediction capabilities or dynamics explanation should be always accounted for.
Livio Fenga. 2017. \u201cLoss of Fitting and Distance Prediction in Fixed vs Updated ARIMA Models\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 17 (GJSFR Volume 17 Issue F1): .
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.
Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.
Total Score: 101
Country: Italy
Subject: Global Journal of Science Frontier Research - F: Mathematics & Decision
Authors: Livio Fenga (PhD/Dr. count: 0)
View Count (all-time): 183
Total Views (Real + Logic): 3689
Total Downloads (simulated): 1840
Publish Date: 2017 02, Sun
Monthly Totals (Real + Logic):
This paper attempted to assess the attitudes of students in
Advances in technology have created the potential for a new
Inclusion has become a priority on the global educational agenda,
In many cases, it might be advisable to keep an operational time series model fixed for a given span of time, instead of updating it as a new datum becomes available. One common case, is represented by model-based deseasonalization procedures, whose time series models are updated on a regular basis by National Statistical Offices. In fact, in order to minimize the extent of the revisions and grant a greater stability of the already released figures, the interval in between two updating processes is kept “reasonably” long (e.g. one year). Other cases can be found in many contexts, e.g. in engineering for structural reliability analysis or in all those cases where model re-estimation is not a practical or even a viable options, e.g. due to time constraints or computational issues. Clearly, the inevitable trade-off between a fixed models and its updated counterpart, e.g. in terms of fitting performances, out-of-sample prediction capabilities or dynamics explanation should be always accounted for.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.