Image de couverture de livre

On the partial autocorrelation function for locally stationary time series: characterization, estimation and inference

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ding, Xiucai, Zhou, Zhou
Format:	Preprint
Publié:	2024
Sujets:	Statistics Theory Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Simultaneous Sieve Estimation and Inference for Time-Varying Nonlinear Time Series Regression
par: Ding, Xiucai, et autres
Publié: (2025)

A spectral inference method for determining the number of communities in networks
par: Wu, Yujia, et autres
Publié: (2026)

A portmanteau test for multivariate non-stationary functional time series with an increasing number of lags
par: Bai, Lujia, et autres
Publié: (2024)

Unifying regression-based and design-based causal inference in time-series experiments
par: Lin, Zhexiao, et autres
Publié: (2025)

With random regressors, least squares inference is robust to correlated errors with unknown correlation structure
par: Zhang, Zifeng, et autres
Publié: (2024)

Embedding Network Autoregression for time series analysis and causal peer effect inference
par: Chang, Jae Ho, et autres
Publié: (2024)

Gradual changes in functional time series
par: Bastian, Patrick, et autres
Publié: (2024)

Wasserstein and Convex Gaussian Approximations for Non-stationary Time Series of Diverging Dimensionality
par: Liu, Miaoshiqi, et autres
Publié: (2025)

Optimal inference for the mean of random functions
par: Kassi, Omar, et autres
Publié: (2025)

Non-parametric estimation of conditional quantiles for time series with heavy tails
par: Mathew, Deemat C, et autres
Publié: (2024)

Weight-calibrated estimation for factor models of high-dimensional time series
par: Qiao, Xinghao, et autres
Publié: (2025)

Optimal estimation of the null distribution in large-scale inference
par: Kotekal, Subhodh, et autres
Publié: (2024)

Deep learning estimation of the spectral density of functional time series on large domains
par: Mohammadi, Neda, et autres
Publié: (2026)

Two-sample inference for sparse functional data
par: Zhang, Chi, et autres
Publié: (2023)

Average partial effect estimation using double machine learning
par: Klyne, Harvey, et autres
Publié: (2023)

Fiducial inference for partially identified parameters with applications to instrumental variable models
par: Cui, Yifan, et autres
Publié: (2025)

An autocovariance-based learning framework for high-dimensional functional time series
par: Chang, Jinyuan, et autres
Publié: (2020)

Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models
par: Armillotta, Mirko, et autres
Publié: (2023)

Detection of mean changes in partially observed functional data
par: Hudecová, Šárka, et autres
Publié: (2025)

Difference-based covariance matrix estimate in time series nonparametric regression with applications to specification tests
par: Bai, Lujia, et autres
Publié: (2023)

Statistical inference of random graphs with a surrogate likelihood function
par: Wu, Dingbo, et autres
Publié: (2022)

On the modelling and prediction of high-dimensional functional time series
par: Chang, Jinyuan, et autres
Publié: (2024)

Semiparametric mean and variance joint models with Laplace link functions for count time series
par: Liu, Tianqing, et autres
Publié: (2024)

Anisotropic local constant smoothing for change-point regression function estimation
par: Thompson, John R. J., et autres
Publié: (2020)

Subscedastic weighted least squares estimates
par: Bryan, Jordan, et autres
Publié: (2024)

From sparse to dense functional time series: phase transitions of detecting structural breaks and beyond
par: Cai, Leheng, et autres
Publié: (2024)

Estimation and inference for minimizer and minimum of convex functions: optimality, adaptivity and uncertainty principles
par: Cai, T. Tony, et autres
Publié: (2023)

Inverting estimating equations for causal inference on quantiles
par: Cheng, Chao, et autres
Publié: (2024)

Validating spatial-temporal separability for stationary processes
par: Bai, Lujia, et autres
Publié: (2026)

Nonparametric, tuning-free estimation of S-shaped functions
par: Feng, Oliver Y., et autres
Publié: (2021)

Doubly robust estimation with functional outcomes missing at random
par: Liu, Xijia, et autres
Publié: (2024)

Optimal estimation in private distributed functional data analysis
par: Xue, Gengyu, et autres
Publié: (2024)

On unbiased estimators for functions of the rate parameter of the exponential distribution
par: Vila, Roberto, et autres
Publié: (2025)

Pivotal inference for linear predictions in stationary processes
par: Dette, Holger, et autres
Publié: (2025)

Neymanian inference in randomized experiments
par: Chattopadhyay, Ambarish, et autres
Publié: (2024)

Mosaic inference on panel data
par: Spector, Asher, et autres
Publié: (2025)

Selective inference using randomized group lasso estimators for general models
par: Huang, Yiling, et autres
Publié: (2023)

Optimal rates for estimating the covariance kernel from synchronously sampled functional data
par: Berger, Max, et autres
Publié: (2024)

Penalized spline estimation of principal components for sparse functional data: rates of convergence
par: He, Shiyuan, et autres
Publié: (2024)

Improved bounds and inference on optimal regimes
par: Laurendeau, Julien D., et autres
Publié: (2024)