RMSSE results:
SES TBATS Theta ETS (DHR-) ARIMA PR Cat- Boost FFNN DeepAR N- BEATS WaveNet Trans- former Informer DLinear TTM (ZS) iTrans- former N-BEATS global N-HITS NLinear PatchTSMixer PatchTST TiDE TimeMixer TSMixer TimesFM(ZS) foundational
Aus. Elecdemand 3.277 2.125 3.292 6.13 4.691 1.545 1.35 1.574 1.831 1.28 1.403 1.404 - 1.481 - 1.733 1.384 1.422 1.479 1.317 1.425 1.528 1.418 1.557 2.522
Bitcoin 6.18 5.546 6.22 5.818 6.546 5.411 5.653 7.027 7.24 9.02 5.526 9.228 - 7.901 5.736 - 7.391 7.19 6.722 - - - - 7.291 6.672
Carparts 1.563 1.688 1.602 1.593 1.611 1.508 1.57 1.524 1.524 3.096 1.523 1.524 - 1.524 1.501 1.508 1.526 1.523 1.602 1.513 1.471 1.524 1.514 1.5 1.495
CIF 2016 1.767 1.128 1.316 1.099 1.219 1.371 1.602 - - - - - - 4.115 1.447 1.545 3 1.941 1.611 1.863 1.455 2.632 1.614 1.53 1.483
COVID 9.489 6.99 9.567 6.551 7.527 10.542 10.309 6.893 8.577 7.178 9.462 10.839 - 7.341 9.294 6.582 9.637 9.008 6.483 6.594 6.437 10.707 6.7 6.878 10.6
Dominick 0.682 0.839 0.719 0.696 - 1.107 0.982 0.719 0.693 1.13 0.701 0.686 - 0.686 - 0.671 0.69 0.688 0.687 0.659 0.655 0.67 0.684 0.679 0.669
Electricity Hourly 5.587 4.636 5.588 7.514 5.72 3.752 3.229 4.258 3.407 2.828 2.685 3.245 5.549 2.916 - 4.143 2.879 2.919 2.864 3.637 3.362 3.016 2.846 3.01 3.051
Electricity Weekly 1.679 0.916 1.607 1.669 1.013 1.051 0.94 0.906 1.14 0.921 1.382 1.901 - 0.964 1.021 1.133 1.01 1.108 0.929 0.958 0.98 0.952 1.14 0.916 1.044
FRED-MD 0.73 0.596 0.951 0.564 0.632 9.644 1.047 0.719 0.756 0.699 0.908 2.027 18.307 0.876 0.795 0.855 0.807 0.79 1.028 0.701 0.745 1.022 0.721 0.691 0.75
Hospital 0.992 0.938 0.931 0.936 0.96 0.953 0.973 1.019 0.935 0.963 0.954 1.206 - 0.98 0.964 1.042 0.957 0.975 0.982 0.97 0.982 1.038 0.983 0.991 0.94
Kaggle Weekly 0.959 0.895 0.951 1.045 - 1.306 2.517 0.974 1.03 0.952 0.901 1.173 - 0.971 - 0.898 0.886 0.864 0.934 0.887 0.965 1.005 0.896 0.878 0.883
KDD 2.405 2.159 2.406 2.553 2.863 2.004 1.937 1.966 2.485 2.396 1.935 2.5 - 2.013 - 2.087 2.003 1.929 1.982 1.957 1.957 2.04 1.989 1.99 2.107
M1 Monthly 1.688 1.338 1.306 1.285 1.389 1.36 1.449 1.444 1.424 1.408 1.454 2.525 - 1.803 1.617 1.734 1.5 1.516 2.015 1.527 1.675 1.806 1.524 1.514 1.49
M1 Quarterly 2.227 1.98 1.967 1.913 2.087 2.193 2.363 2.168 2.122 2.086 1.984 3.208 - 3.63 2.143 2.24 3.007 2.777 4.079 2.182 2.347 3.125 2.163 2.194 2.173
M1 Yearly 5.708 4.105 4.879 4.416 5.414 5.325 5.19 5.13 5.383 5.101 5.367 6.386 - 6.752 5.402 4.68 6.734 5.729 9.241 4.796 4.959 7.136 4.686 4.752 6.024
M3 Monthly 1.302 1.036 1.035 1.036 1.048 1.198 - 1.203 1.373 1.132 1.212 1.693 - 1.263 1.23 1.256 1.103 1.093 1.178 1.2 1.275 1.258 1.142 1.193 1.177
M3 Other - - - - - - - - - - - - - - - - - - - - - - - - -
M3 Quarterly 1.658 1.464 1.303 1.37 1.448 1.453 1.693 1.561 1.523 1.384 1.489 2.773 - 1.459 1.564 1.474 1.333 1.33 1.416 1.406 1.468 1.767 1.332 1.358 1.506
M3 Yearly 3.626 3.646 3.204 3.32 4.017 3.738 4.347 3.946 4.065 3.438 3.49 3.534 - 3.472 3.451 3.417 3.518 3.288 3.488 3.418 3.557 3.752 3.418 3.419 3.883
M4 Daily 1.351 1.356 1.35 1.461 1.385 1.358 1.792 1.342 2.514 1.417 1.353 1.592 - 1.296 1.247 1.431 1.325 1.338 1.343 1.345 1.382 1.527 1.346 1.331 1.537
M4 Hourly 14.341 3.34 14.236 31.151 14.185 1.949 2.22 3.475 2.688 2.812 2.075 9.379 - 3.941 2.752 7.543 3.388 4.621 2.45 2.805 3.467 3.796 8.333 3.837 1.058
M4 Monthly 1.382 1.353 1.163 1.138 1.163 1.296 1.304 1.413 1.39 1.241 1.389 2.345 - 1.212 - 1.387 1.172 1.192 1.217 1.236 1.324 1.347 1.221 1.22 1.275
M4 Quarterly 1.656 1.385 1.429 1.355 1.43 1.524 1.558 1.645 1.486 1.448 1.443 1.738 - 1.467 - 1.651 1.41 1.428 1.548 1.531 1.632 1.692 1.517 1.513 1.595
M4 Weekly 0.71 0.602 0.658 0.694 0.659 0.576 0.713 0.647 0.7 0.543 0.701 0.83 - 0.598 0.765 0.854 0.576 0.572 0.587 0.644 0.645 0.67 0.568 0.604 0.571
M4 Yearly 4.55 3.92 3.861 3.927 4.443 4.115 4.179 - - - - - 1.925 3.82 - 3.939 3.923 3.815 4.358 3.938 4.676 4.195 3.931 3.892 -
NN5 Daily 1.889 1.202 1.224 1.21 1.391 1.672 1.32 1.337 1.276 1.491 1.322 1.364 - 1.324 1.881 1.325 1.279 1.291 1.332 1.325 1.367 1.327 1.318 1.316 1.96
NN5 Weekly 1.084 1.076 1.078 1.088 1.07 1.06 1.045 1.037 1.085 0.986 1.405 1.356 - 1.077 1.11 1.032 1.019 1.068 1.067 1.023 1.055 1.057 1.121 1.094 1.049
Pedestrians 1.287 1.525 1.288 1.533 5.144 0.353 0.36 0.377 0.392 0.556 0.353 0.396 - 0.351 0.431 0.53 0.338 0.335 0.343 0.364 0.356 0.337 0.35 0.347 0.367
Rideshare 4.76 4.827 5.634 4.76 3.359 4.763 4.622 4.726 4.739 4.349 3.727 4.76 2.8 4.777 - 7.421 4.857 4.757 4.802 6.25 5.242 4.798 5.938 4.097 3.631
Saugeen 2.64 2.824 2.639 3.343 2.867 3.164 2.608 2.695 3.004 3.244 2.852 3.258 - 3.117 2.537 3.075 3.049 3.127 2.497 2.886 2.943 2.954 3.01 2.922 2.962
Solar 10 Mins 3.2 4.802 3.201 3.2 2.441 3.2 3.847 3.194 3.198 2.926 - 3.2 - 2.94 - 3.136 3.942 3.963 3.449 3.201 3.172 2.935 3.083 3.119 3.192
Solar Weekly 1.345 1.057 1.356 1.27 0.975 1.174 1.763 1.224 0.884 1.321 2.485 0.687 0.332 1.287 1.034 1.154 1.431 1.571 1.401 1.174 1.479 1.228 1.187 1.277 1.075
Sunspot 0.128 0.077 0.128 0.128 0.077 0.103 0.062 0.219 0.03 0.376 0.017 0.013 - 0.124 0.124 0.091 0.197 0.172 0.107 0.08 0.111 0.188 0.08 0.094 0.28
Temp. Rain 1.963 1.815 1.974 2.021 1.779 1.779 1.63 1.684 1.677 2.221 1.631 1.588 - 1.855 - 1.616 1.615 1.618 1.989 1.624 1.795 1.855 1.589 1.59 1.759
Tourism Monthly 4.427 2.273 2.158 1.954 2.03 2.165 2.195 2.055 1.824 2.079 1.898 1.986 - 1.937 4.1 3.249 1.887 1.902 1.981 2.166 2.776 2.205 1.997 2.027 3.107
Tourism Quarterly 3.769 2.209 2.046 1.905 2.112 2.003 - 2.036 1.915 1.811 2.048 2.17 - 1.862 3.691 2.719 1.903 1.869 1.979 1.944 2.924 3.407 2.021 1.97 2.648
Tourism Yearly 3.568 4.05 3.307 3.713 4.173 3.784 3.911 3.717 3.456 3.25 3.974 3.847 3.984 7.336 3.377 3.083 131.329 3.592 6.775 3.166 3.693 5.781 3.05 3.06 3.596
Traffic Hourly 2.489 3.173 2.489 2.904 3.091 1.821 2.132 1.413 1.363 1.698 1.747 1.32 - 1.435 - 1.392 1.33 1.337 1.469 1.584 1.457 1.44 1.339 1.315 1.302
Traffic Weekly 1.5 1.494 1.514 1.509 1.494 1.499 1.438 1.551 1.507 1.419 1.641 2.098 6.882 1.517 1.477 1.579 1.475 1.447 1.466 1.493 1.442 1.508 1.493 1.46 1.329
US Births 4.988 2.209 2.679 2.212 2.57 2.667 2.252 2.647 2.491 2.286 2.8 2.501 - 2.819 5.012 2.461 2.198 2.29 2.791 2.889 2.738 3.408 2.249 2.466 4.991
Vehicle Trips 2.822 2.339 2.866 2.963 2.845 2.63 2.482 2.33 2.408 2.655 2.324 3.002 - 2.449 2.436 2.488 2.214 2.196 2.432 2.443 2.468 2.49 2.367 2.385 2.662
Weather 0.873 0.88 0.978 0.899 0.947 3.342 0.95 0.873 0.869 0.959 0.951 0.901 - 0.856 0.785 0.886 0.867 0.865 0.857 0.888 0.863 0.866 0.873 0.877 0.856

*The results of the Informer model are only recorded for the datasets with equal-length series. For the datasets with unequal-length series, the Informer model is required to be executed per each series where the execution time is considerably high (for details, see here). Furthermore, the intermittent datasets such as Carparts, Rideshare, Web Traffic, Covid Deaths and Temperature Rain are not considered for the Informer experiments.

About Us


Team members

We are a group of time series researchers from Monash University and University of Sydney:

Contributors

The following people have contributed to our repository:

Contribute to Our Repository


We encourage other researchers to contribute time series datasets or benchmarking results to our repository either by directly uploading the datasets into our repository and/or by contacting us via email. You will then be listed as a contributor, and in the acknowledgements section.

If there are any copyright issues of the datasets, please contact us via email.

Acknowledgement


We are very grateful to the Department of Data Science and Artificial Intelligence of Monash University for their sponsorship.

Gareth Davies from Neural Aspect has contributed benchmark runs of many of the deep-learning methods, namely Autoformer, DLinear, NLinear, NBEATS, N-HITS, TiDE, PatchTST, and TimesFM.