Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess - Supplemental Material
T. Krake, D. Klötzl, D. Hägele, and D. Weiskopf. Dataset, (2024)Related to: Tim Krake, Daniel Klötzl, David Hägele, and Daniel Weiskopf, Üncertainty-Aware Seasonal-Trend Decomposition Based on Loess", in IEEE Transactions on Visualization and Computer Graphics, 2024. doi: 10.1109/TVCG.2024.3364388.
DOI: 10.18419/darus-3845
Abstract
In this supplemental material, we provide the appendix (mathematically exact propagation of uncertainty) and the video material for uncertainty-aware seasonal-trend decomposition based on loess (UASTL). This material complements the main document: The paper on Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess.
Related to: Tim Krake, Daniel Klötzl, David Hägele, and Daniel Weiskopf, Üncertainty-Aware Seasonal-Trend Decomposition Based on Loess", in IEEE Transactions on Visualization and Computer Graphics, 2024. doi: 10.1109/TVCG.2024.3364388
%0 Generic
%1 krake2024uncertaintyaware
%A Krake, Tim
%A Klötzl, Daniel
%A Hägele, David
%A Weiskopf, Daniel
%D 2024
%K darus mult ubs_10005 ubs_10017 ubs_10018 ubs_20008 ubs_20024 ubs_20035 ubs_30086 ubs_30200 ubs_40132 unibibliografie
%R 10.18419/darus-3845
%T Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess - Supplemental Material
%X In this supplemental material, we provide the appendix (mathematically exact propagation of uncertainty) and the video material for uncertainty-aware seasonal-trend decomposition based on loess (UASTL). This material complements the main document: The paper on Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess.
@misc{krake2024uncertaintyaware,
abstract = {In this supplemental material, we provide the appendix (mathematically exact propagation of uncertainty) and the video material for uncertainty-aware seasonal-trend decomposition based on loess (UASTL). This material complements the main document: The paper on Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess. },
added-at = {2024-03-18T13:06:10.000+0100},
affiliation = {Krake, Tim/Universität Stuttgart, Klötzl, Daniel/Universität Stuttgart, Hägele, David/Universität Stuttgart, Weiskopf, Daniel/Universität Stuttgart},
author = {Krake, Tim and Klötzl, Daniel and Hägele, David and Weiskopf, Daniel},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/254598944f72ff95b837a5e74fe01f3a6/unibiblio},
doi = {10.18419/darus-3845},
howpublished = {Dataset},
interhash = {40b84e5caf0cadc5098d04089b49435c},
intrahash = {54598944f72ff95b837a5e74fe01f3a6},
keywords = {darus mult ubs_10005 ubs_10017 ubs_10018 ubs_20008 ubs_20024 ubs_20035 ubs_30086 ubs_30200 ubs_40132 unibibliografie},
note = {Related to: Tim Krake, Daniel Klötzl, David Hägele, and Daniel Weiskopf, "Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess", in IEEE Transactions on Visualization and Computer Graphics, 2024. doi: 10.1109/TVCG.2024.3364388},
orcid-numbers = {Krake, Tim/0009-0004-7084-3633, Klötzl, Daniel/0000-0002-4222-3320, Hägele, David/0000-0002-2679-6882, Weiskopf, Daniel/0000-0003-1174-1026},
timestamp = {2024-03-18T13:06:10.000+0100},
title = {Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess - Supplemental Material},
year = 2024
}
