Search Results for author:
Found 6 papers, 3 papers with code
DeepVARwT: Deep Learning for a VAR Model with Trend
This is a model for stationary time series which can be extended to allow the presence of a deterministic trend in each series.
fETSmcs: Feature-based ETS model component selection
We evaluate our approach on the widely used forecasting competition data set M4, in terms of both point forecasts and prediction intervals.
Exploring the social influence of Kaggle virtual community on the M5 competition
This paper aims to study the social influence of virtual community on user behaviors in the M5 competition.
Crude oil price forecasting incorporating news text
Sparse and short news headlines can be arbitrary, noisy, and ambiguous, making it difficult for classic topic model LDA (latent Dirichlet allocation) designed for accommodating long text to discover knowledge from them.
Research and application of time series algorithms in centralized purchasing data
Based on the online transaction data of COSCO group's centralized procurement platform, this paper studies the clustering method of time series type data.
Forecasting with time series imaging
Recently, the use of time series features for forecast model averaging has been an emerging research focus in the forecasting community.
