Imagen de Portada

Statistical inference for large-dimensional tensor factor model by iterative projections

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Barigozzi, Matteo, He, Yong, Li, Lingxiao, Trapani, Lorenzo
Formato:	Preprint
Publicado:	2022
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Moving sum procedure for multiple change point detection in large factor models
por: Barigozzi, Matteo, et al.
Publicado: (2024)

Tail-robust factor modelling of vector and tensor time series in high dimensions
por: Barigozzi, Matteo, et al.
Publicado: (2024)

Estimation of large approximate dynamic matrix factor models based on the EM algorithm and Kalman filtering
por: Barigozzi, Matteo, et al.
Publicado: (2025)

Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models
por: Barigozzi, Matteo
Publicado: (2023)

FNETS: Factor-adjusted network estimation and forecasting for high-dimensional time series
por: Barigozzi, Matteo, et al.
Publicado: (2022)

Real-time monitoring with RCA models
por: Horváth, Lajos, et al.
Publicado: (2023)

Bayesian inference for aggregated Hawkes processes
por: Zhou, Lingxiao, et al.
Publicado: (2022)

Statistical inference for high-dimensional convoluted rank regression
por: Cai, Leheng, et al.
Publicado: (2024)

Sequential monitoring for explosive volatility regimes
por: Horvath, Lajos, et al.
Publicado: (2024)

Estimation and inference of high-dimensional partially linear regression models with latent factors
por: Shi, Yanmei, et al.
Publicado: (2025)

High-dimensional inference for single-index model with latent factors
por: Shi, Yanmei, et al.
Publicado: (2025)

Inference in matrix-valued time series with common stochastic trends and multifactor error structure
por: Chen, Rong, et al.
Publicado: (2025)

Statistical inference for high-dimensional spectral density matrix
por: Chang, Jinyuan, et al.
Publicado: (2022)

Partially factorized variational inference for high-dimensional mixed models
por: Goplerud, Max, et al.
Publicado: (2023)

Fast Online Changepoint Detection
por: Ghezzi, Fabrizio, et al.
Publicado: (2024)

High-dimensional iterative variable selection for accelerated failure time models
por: Sanyal, Nilotpal
Publicado: (2023)

Bayesian inference of vector autoregressions with tensor decompositions
por: Luo, Yiyong, et al.
Publicado: (2022)

Uniform inference in linear mixed models
por: Ekvall, Karl Oskar, et al.
Publicado: (2025)

Advances in projection predictive inference
por: McLatchie, Yann, et al.
Publicado: (2023)

Tucker tensor factor models: matricization and mode-wise PCA estimation
por: Zhang, Xu, et al.
Publicado: (2022)

Partially Bayes p-values for large scale inference
por: Ignatiadis, Nikolaos, et al.
Publicado: (2025)

Challenges and Opportunities of Computational Social Science for Official Statistics
por: Signorelli, Serena, et al.
Publicado: (2022)

Statistical inference for core-periphery structures
por: Yanchenko, Eric, et al.
Publicado: (2025)

Statistical inference of heterogeneous treatment effects using semiparametric single-index model
por: Yu, Jichang, et al.
Publicado: (2025)

Statistical inference for partially shape-constrained function-on-scalar linear regression models
por: Han, Kyunghee, et al.
Publicado: (2024)

Doubly-robust inference and optimality in structure-agnostic models with smoothness
por: Bonvini, Matteo, et al.
Publicado: (2024)

Statistical inference of convex order by Wasserstein projection
por: Kim, Jakwang, et al.
Publicado: (2024)

An efficient tensor regression for high-dimensional data
por: Si, Yuefeng, et al.
Publicado: (2022)

Joint modeling and inference of multiple-subject high-dimensional sparse vector autoregressive models
por: Kim, Younghoon, et al.
Publicado: (2025)

Bayesian iterative screening in ultra-high dimensional linear regressions
por: Wang, Run, et al.
Publicado: (2021)

Statistical inference with win statistics in cluster-randomized trials with composite outcomes
por: Fang, Xi, et al.
Publicado: (2026)

Using Model-Assisted Calibration Methods to Improve Efficiency of Regression Analyses with Two-Phase Samples under Complex Survey Designs
por: Wang, Lingxiao
Publicado: (2023)

Modeling large dimensional matrix time series with partially known and latent factors
por: Hui, Yongchang, et al.
Publicado: (2024)

Adaptive weighted approach for high-dimensional statistical learning and inference
por: Lu, Jun, et al.
Publicado: (2022)

Sequential multiple importance sampling for high-dimensional Bayesian inference
por: Binbin, Li, et al.
Publicado: (2025)

Robust estimation for number of factors in high dimensional factor modeling via Spearman correlation matrix
por: Qiu, Jiaxin, et al.
Publicado: (2023)

High dimensional inference for extreme value indices
por: Chen, Liujun, et al.
Publicado: (2024)

Statistical inference for association studies in the presence of binary outcome misclassification
por: Webb, Kimberly A. Hochstedler, et al.
Publicado: (2023)

Distributed inference for heterogeneous mixture models using multi-site data
por: Liu, Xiaokang, et al.
Publicado: (2025)

Conformal causal inference for cluster randomized trials: model-robust inference without asymptotic approximations
por: Wang, Bingkai, et al.
Publicado: (2024)