LAUSR

About LAUSR
Donate
Contact Us

Follow us:

You are not signed in:

Sign Up!


   Articles with "temporal dependence" as a keyword



Photo from wikipedia

Unveiling endogeneity and temporal dependence in energy prices and demand in Iberian countries: a stochastic hidden Markov model approach

Sign Up to like & get
recommendations! Published in 2021 at "Annals of Operations Research"

DOI: 10.1007/s10479-021-04211-z

Abstract: In this paper, we analyze the temporal dependence in energy prices and demand using daily data of Portugal and Spain over the period 2007–2017. The methodology used is based on a stochastic Hidden Markov Model… read more here.

Keywords: energy prices; future; energy; prices demand ... See more keywords

Applying temporal dependence to detect changes in streaming data

Sign Up to like & get
recommendations! Published in 2018 at "Applied Intelligence"

DOI: 10.1007/s10489-018-1254-7

Abstract: Detection of changes in streaming data is an important mining task, with a wide range of real-life applications. Numerous algorithms have been proposed to efficiently detect changes in streaming data. However, the limitation of existing… read more here.

Keywords: streaming data; changes streaming; applying temporal; temporal dependence ... See more keywords

Inference without smoothing for large panels with cross-sectional and temporal dependence

Sign Up to like & get
recommendations! Published in 2021 at "Journal of Econometrics"

DOI: 10.1016/j.jeconom.2020.10.003

Abstract: This paper addresses inference in large panel data models in the presence of both cross-sectional and temporal dependence of unknown form. We are interested in making inferences without relying on the choice of any smoothing… read more here.

Keywords: cross sectional; dependence; without smoothing; inference without ... See more keywords

TGN: A Temporal Graph Network for Physics Prediction

Sign Up to like & get
recommendations! Published in 2024 at "Applied Sciences"

DOI: 10.3390/app14020863

Abstract: Long-term prediction of physical systems on irregular unstructured meshes is extremely challenging due to the spatial complexityof meshes and the dynamic changes over time; namely, spatial dependence and temporal dependence. Recently, graph-based next-step prediction models… read more here.

Keywords: physical systems; dependence; temporal graph; prediction ... See more keywords