A note on nonlinear regression for the autoregressive moving average with non-hd errors

Sahadeb Sarkar; Dong Wan Shin

doi:10.1080/03610928308831161

A note on nonlinear regression for the autoregressive moving average with non-hd errors

Sahadeb Sarkar, Dong Wan Shin

Department of Statistics

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Estimation by nonlinear regression of the parameters for the stationary and invertible autoregressive moving average (ARMA) model with mixing or martingale difference errors is considered. Simple proofs of consistency and asymptotic normality for the nonlinear least squares estimator are given by exploiting results from nonlinear estimation theory and mixing and mixingale theory.

Original language	English
Pages (from-to)	501-513
Number of pages	13
Journal	Communications in Statistics - Theory and Methods
Volume	22
Issue number	9
DOIs	https://doi.org/10.1080/03610928308831161
State	Published - 1 Jan 1993

Keywords

Large sample properties
Missingale theory
Nonlinear estimation

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10.1080/03610928308831161

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title = "A note on nonlinear regression for the autoregressive moving average with non-hd errors",

abstract = "Estimation by nonlinear regression of the parameters for the stationary and invertible autoregressive moving average (ARMA) model with mixing or martingale difference errors is considered. Simple proofs of consistency and asymptotic normality for the nonlinear least squares estimator are given by exploiting results from nonlinear estimation theory and mixing and mixingale theory.",

keywords = "Large sample properties, Missingale theory, Nonlinear estimation",

author = "Sahadeb Sarkar and Shin, {Dong Wan}",

year = "1993",

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AB - Estimation by nonlinear regression of the parameters for the stationary and invertible autoregressive moving average (ARMA) model with mixing or martingale difference errors is considered. Simple proofs of consistency and asymptotic normality for the nonlinear least squares estimator are given by exploiting results from nonlinear estimation theory and mixing and mixingale theory.

KW - Large sample properties

KW - Missingale theory

KW - Nonlinear estimation

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DO - 10.1080/03610928308831161

M3 - Article

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JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 9

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A note on nonlinear regression for the autoregressive moving average with non-hd errors

Abstract

Keywords

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