案例2:我们想要预测iPhone12和iPhone13的销量,这就是multivariate (多元)时序的问题。从表中看到经典的时序分析中,只有VARIMA适用,神经网络类的模型,比如RNN等都是适用的。 案例3:我们想要预测iPhone手机的销量,并且我们知道双11,春节,新品发布会等都会对销量有重大的影响。这类问题就属于Future-Known covariate support...
论文1-Expressing Multivariate Time Series as Graphs with Time Series Attention Transformer:通过SMD将时间序列分解成多个IMF周期性序列+趋势项后,建立多变量之间的关系图,利用改进的Transformer实现节点信息、边关系、图结构三者信息融合进行预测。 论文2-Spatial-Temporal Identity: A Simple yet Effective Baseline for...
timeseriestime-serieslstmdartsarimaprophetmultivariate-analysisfbprophetsarimaxmoving-averagegranger-causalitysarimakatsholtwintersdeeparautotsautoarimamultiple-time-series UpdatedMar 9, 2024 Jupyter Notebook Star14 New product demand forecasting via Content based learning for multi-branch stores: Ali and Nino ...
combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models can be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for...
“RegressionModel只能解释数值静态协变量数据。请考虑使用darts.dataprocessing.transformers.static_covariates...
“RegressionModel只能解释数值静态协变量数据。请考虑使用darts.dataprocessing.transformers.static_covariates...