Multidimensional dynamic factor models
This paper generalises dynamic factor models for multidimensional dependent data. In doing so, it develops an interpretable technique to study complex information sources ranging from repeated surveys with a varying number of respondents to panels of satellite images. We specialise our results to model microeconomic data on US households jointly with macroeconomic aggregates. This results in a powerful tool able to generate localised predictions, counterfactuals and impulse response functions for individual households, accounting for traditional time-series complexities depicted in the state-space literature. The model is also compatible with the growing focus of policymakers for real-time economic analysis as it is able to process observations online, while handling missing values and asynchronous data releases.
Code (0)
등록된 구현이 없습니다.
Tasks
Missing ValuesTime SeriesTime Series AnalysisMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Optimal Control for Remote Patient Monitoring with Multidimensional Health States
Selecting the right monitoring level in Remote Patient Monitoring (RPM) systems for e-healthcare is crucial for balancing patient outcomes, various resources, and patient's quality of life. A prior work has used one-dime…
Exploring Multidimensional Checkworthiness: Designing AI-assisted Claim Prioritization for Human Fact-checkers
Given the massive volume of potentially false claims circulating online, claim prioritization is essential in allocating limited human resources available for fact-checking. In this study, we perceive claim prioritizatio…
Fact CheckingInformation RetrievalMultidimensional Binary Search for Contextual Decision-Making
We consider a multidimensional search problem that is motivated by questions in contextual decision-making, such as dynamic pricing and personalized medicine. Nature selects a state from a $d$-dimensional unit ball and t…
Decision MakingDynamic Dimension Wrapping (DDW) Algorithm: A Novel Approach for Efficient Cross-Dimensional Search in Dynamic Multidimensional Spaces
To effectively search for the optimal motion template in dynamic multidimensional space, this paper proposes a novel optimization algorithm, Dynamic Dimension Wrapping (DDW).The algorithm combines Dynamic Time Warping (D…
Dynamic Time WarpingFactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing
Remote photoplethysmography (rPPG) enables non-invasive extraction of blood volume pulse signals through imaging, transforming spatial-temporal data into time series signals. Advances in end-to-end rPPG approaches have f…