DeepAI AI Chat

Optimal Input Design for Parameter Estimation in AR(1) with Dependent Stationary Noise

10/26/2017

∙

by Chunhao Cai, et al.

∙

Nankai University

∙

∙

This paper focus on the asymptotical input and the asymptotical properties of the MLE of the drift parameter in the Autoregressive of order 1 (AR(1)) driven by an regular stationary noises (with dependence). The Laplace Transform computations will be the main tool for our analysis.

page 1

page 2

page 3

page 4

∙ 09/06/2023

Geometric Infinitely Divisible Autoregressive Models

In this article, we discuss some geometric infinitely divisible (gid) ra...

0 Monika Singh Dhull, et al. ∙

∙ 09/08/2020

Controlled Drift Estimation in the Mixed Fractional Ornestein-Uhlenbeck Process

This paper is devoted to the determination of the asymptotical optimal i...

0 Chunhao Cai, et al. ∙

∙ 03/04/2011

Generalization error bounds for stationary autoregressive models

We derive generalization error bounds for stationary univariate autoregr...

0 Daniel J. McDonald, et al. ∙

∙ 03/14/2023

Parameter estimation of stochastic SIR model driven by small Lévy noises with time-dependent periodic transmission

We investigate the parameter estimation and forecasting of two forms of ...

0 Terry Easlick, et al. ∙

∙ 10/26/2021

Statistical inference on AR(p) models with non-i.i.d. innovations

The autoregressive process is one of the fundamental and most important ...

0 Yunyi Zhang, et al. ∙

∙ 10/20/2018

Asymptotic efficiency in the Autoregressive process driven by a stationary Gaussian noise

The first purpose of this article is to obtain a.s. asymptotic propertie...

0 Marius Soltane, et al. ∙

∙ 05/25/2023

SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise

The well-established practice of time series analysis involves estimatin...

0 Abdullah Alomar, et al. ∙