Sparse statistical approach for multivariate modelling

多元建模的稀疏统计方法

• 批准号: 22K13377
• 负责人: POIGNARD BENJAMIN
• 金额: $ 2.83万
• 依托单位: Osaka University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Early-Career Scientists
• 财政年份: 2022
• 资助国家: 日本
• 起止时间: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-22K13377/
• 关键词: Asymptotic theory; Copulas; Factor models; Sparsity; Time series; High dimension; Multivariate modelling

The research focused on the sparse modelling of multivariate models and the development of parsimonious statistical methods. The sparse modelling aimed to improve the prediction accuracy and the precision of the estimators. The main part of the research was devoted to the derivation of the theoretical properties of such sparse techniques (mainly large sample analysis) and to the assessment of the empirical performances of illustrate the relevance of the sparse modelling. We could develop fast solving algorithms and showed that the sparse approach provides good theoretical properties. We could model high-dimensional random vectors and fix the curse of dimensionality.

研究的重点是多变量模型的稀疏建模和简约统计方法的发展。稀疏建模的目的是提高预测精度和估计器的精度。研究的主要部分致力于这种稀疏技术(主要是大样本分析)的理论性质的推导和对稀疏建模的相关性说明的经验表现的评估。我们可以开发快速求解算法，并表明稀疏方法提供了良好的理论性质。我们可以对高维随机向量进行建模，并修复维度诅咒。

项目成果

Sparse M-estimator in semi-parametric copula models

半参数 copula 模型中的稀疏 M 估计器

• 发表时间: 2022
• 作者: Poignard Benjamin;Asai Manabu;Benjamin Poignard;Benjamin Poignard
• 通讯作者: Benjamin Poignard

Sparse factor models of high dimension

高维稀疏因子模型

• 发表时间: 2022
• 作者: Poignard Benjamin;Asai Manabu;Benjamin Poignard
• 通讯作者: Benjamin Poignard

Estimation of high-dimensional vector autoregression via sparse precision matrix

通过稀疏精度矩阵估计高维向量自回归

• DOI: 10.1093/ectj/utad003
• 发表时间: 2023
• 期刊: The Econometrics Journal
• 作者: Poignard Benjamin;Asai Manabu
• 通讯作者: Asai Manabu

Asymptotic theory of sparse factor models in high-dimension

高维稀疏因子模型的渐近理论

• 发表时间: 2022
• 作者: Poignard Benjamin;Asai Manabu;Benjamin Poignard;Benjamin Poignard;Benjamin Poignard
• 通讯作者: Benjamin Poignard