2021 Fiscal Year Research-status Report
Parsimonious statistical modelling for high-dimensional problems
| Project/Area Number |
19K23193
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2019-08-30 – 2023-03-31
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| Keywords | High-dimensions / M-estimation / Sparsity |
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| Outline of Annual Research Achievements |
The research was dedicated to the high-dimensional modelling of multivariate models that typically suffer from the "curse of dimensionality". The sparsity assumption is the main viewpoint: to identify the relevant model parameters, the sparse viewpoint allows to automatically select those parameters and perform feature extraction.
The objective of the modelling is to fix the over-fitting issue, the curse of dimensionality and to gain prediction accuracy for prediction purposes.
A significant part of the work was dedicated to the derivation of the theoretical properties of such high-dimensional techniques (asymptotic/finite sample properties) and to the assessment of the performances of such modelling through simulated and real data experiments.
The following works have been considered: high-dimensional modelling of multivariate stochastic volatility (MSV) models; sparse factor models; sparse estimation for copulas with pseudo-observations; non-linear feature selection and post-selection inference.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
Due to the sanitary situation arising from the spread of coronavirus-19, all face-to-face research conferences, seminars, meetings (both
domestic and international) have been cancelled. Thus, a part of the budget that was originally dedicated for
conference/seminars/research meetings has not been used.
Research progress is going well (3 international publications in 2021) and due to the broad range of open subjects and existing problems in the proposed research, new research papers are currently under development.
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| Strategy for Future Research Activity |
Several projects within the area of the proposed research are currently under development. More precisely, the following works will be considered:
- sparse factor models, where we propose to develop an inferential framework to take into account the rotational indeterminacy constraint.
- the asymptotic properties of sparsity based estimators for copula models in the presence of pseudo-observations. The key challenge is to handle the non-parametric estimation of the marginals during the large sample analysis.
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| Causes of Carryover |
Due to the spread of coronavirus 19, several international conferences and visiting research periods have been cancelled. We plan to use the budget for attending the conferences and purchasing a some equipments (workstation).
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Research Products
(12 results)
