Cover Image

Near-Unit-Root Theory for Affine Processes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Anne, Gael, Lu, Yang, Yu, Xuewen, Zhou, Xiaowen
Format:	Preprint
Published:	2026
Subjects:	Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Estimation of a Dynamic Tobit Model with a Unit Root
by: Bykhovskaya, Anna, et al.
Published: (2025)

Locally Near Optimal Piecewise Linear Regression in High Dimensions via Difference of Max-Affine Functions
by: Kanj, Haitham, et al.
Published: (2026)

Affine calculus for constrained minima of the Kullback-Leibler divergence
by: Pistone, Giovanni
Published: (2025)

Sparse Max-Affine Regression
by: Kanj, Haitham, et al.
Published: (2024)

Measuring Tail Dependence in Linear Processes: Theory and Empirics
by: Datta, Debanjana, et al.
Published: (2026)

Quasi-Maximum Likelihood Estimation of long-memory linear processes
by: Bardet, Jean-Marc, et al.
Published: (2023)

Parameter Estimation for Partially Observed Affine and Polynomial Processes
by: Kallsen, Jan, et al.
Published: (2025)

The Root Finding Problem Revisited: Beyond the Robbins-Monro procedure
by: Yu, Yue, et al.
Published: (2025)

Learning Mixtures of Nonparametric and Convolutional Measures on Effectively Low-dimensional Affine Spaces
by: Chakraborty, Sunrit, et al.
Published: (2026)

Affine invariant interacting Langevin dynamics in Markov chain importance sampling for rare event estimation
by: Beh, Jason, et al.
Published: (2025)

Asymptotic Theory for Linear Functionals of Kernel Ridge Regression
by: Tuo, Rui, et al.
Published: (2024)

The Concept of Statistical Evidence: Historical Roots and Current Developments
by: Evans, Michael
Published: (2024)

Information Geometry of Wasserstein Statistics on Shapes and Affine Deformations
by: Amari, Shun-ichi, et al.
Published: (2023)

Affine Invariance in Continuous-Domain Convolutional Neural Networks
by: Mohaddes, Ali, et al.
Published: (2023)

Generalised Linear Models Driven by Latent Processes: Asymptotic Theory and Applications
by: Barreto-Souza, Wagner, et al.
Published: (2026)

Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon
by: Yu, Hao
Published: (2025)

Theory of functional principal component analysis for discretely observed data
by: Zhou, Hang, et al.
Published: (2022)

A Modern Theory for High-dimensional Cox Regression Models
by: Ye, Hanxuan, et al.
Published: (2022)

Directed Cycles as Higher-Order Units of Information Processing in Complex Networks
by: Rajpal, Hardik, et al.
Published: (2025)

Understanding Generalization in Physics Informed Models through Affine Variety Dimensions
by: Koshizuka, Takeshi, et al.
Published: (2025)

Exact Distribution of the Noncentral Complex Roy's Largest Root Statistic via Pieri's Formula
by: Shimizu, Koki, et al.
Published: (2025)

A GARMA Framework for Unit-Bounded Time Series Based on the Unit-Lindley Distribution with Application to Renewable Energy Data
by: Pumi, Guilherme, et al.
Published: (2025)

Bernstein-von Mises Theorem for Sparse Generalized Linear Model
by: Li, Hanqing, et al.
Published: (2026)

Asymptotics for Reinforced Stochastic Processes on Hierarchical Networks
by: Yang, Li, et al.
Published: (2025)

On the Square Root of Wishart Matrices: Exact Distributions and Asymptotic Gaussian Behavior
by: Liu, Fengcheng
Published: (2025)

Functional Renormalization for Signal Detection: Dimensional Analysis and Dimensional Phase Transition for Nearly Continuous Spectra Effective Field Theory
by: Finotello, Riccardo, et al.
Published: (2025)

Extrapolation in Statistical Learning with Extreme Value Theory
by: Engelke, Sebastian, et al.
Published: (2026)

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
by: Fan, Jianqing, et al.
Published: (2025)

Statistical inference for rough volatility: Minimax Theory
by: Chong, Carsten, et al.
Published: (2022)

Fast Near-Optimal Estimation over Symmetric Norm Balls
by: Neykov, Matey
Published: (2026)

Double Local-to-Unity: Inference under Nearly Nonstationary Volatility
by: Sarkar, Abir, et al.
Published: (2025)

Asymptotic Distribution of Constrained Nearly-Isotonic Graph Fused Lasso
by: Pastukhov, Vladimir
Published: (2025)

Nearly minimax empirical Bayesian prediction of independent Poisson observables
by: Li, Xiao
Published: (2023)

Optimal Estimation for General Gaussian Processes
by: Takabatake, Tetsuya, et al.
Published: (2025)

Model Selection for Unit-root Time Series with Many Predictors
by: Huang, Shuo-Chieh, et al.
Published: (2025)

Taylor's Theorem and Mean Value Theorem for Random Functions and Random Variables
by: Yang, Yifan, et al.
Published: (2021)

Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
by: Fu, Hengyu, et al.
Published: (2024)

Adaptive tail index estimation: minimal assumptions and non-asymptotic guarantees
by: Lederer, Johannes, et al.
Published: (2025)

Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
by: Liu, Lin, et al.
Published: (2023)

On the calibration of survival models with competing risks
by: Alberge, Julie, et al.
Published: (2026)