Nonparametric Estimation of the Density Function of the Distribution of the Noise in CHARN Models

被引：2

作者：

Ngatchou-Wandji, Joseph ^{[1
,2
]}

Ltaifa, Marwa ^{[2
]}

Njamen Njomen, Didier Alain ^{[3
]}

Shen, Jia ^{[4
]}

机构：

[1] EHESP French Sch Publ Hlth, F-35043 Rennes, France

[2] Univ Lorraine, Inst Elie Cartan Lorraine, F-54052 Vandoeuvre Les Nancy, France

[3] Univ Maroua, Dept Math & Comp Sci, Fac Sci, POB 814, Maroua, Cameroon

[4] Fudan Univ, Dept Stat, Shanghai 200433, Peoples R China

来源：

MATHEMATICS | 2022年 / 10卷 / 04期

关键词：

nonlinear heteroscedastic model; kernel estimation; REGRESSION FUNCTION; VOLATILITY FUNCTIONS; EFFICIENT ESTIMATION; UNIFORM CONSISTENCY; VARIANCE-FUNCTION; SPOT VOLATILITY; CONVERGENCE; THRESHOLD; CURVES;

D O I：

10.3390/math10040624

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This work is concerned with multivariate conditional heteroscedastic autoregressive nonlinear (CHARN) models with an unknown conditional mean function, conditional variance matrix function and density function of the distribution of noise. We study the kernel estimator of the latter function when the former are either parametric or nonparametric. The consistency, bias and asymptotic normality of the estimator are investigated. Confidence bound curves are given. A simulation experiment is performed to evaluate the performance of the results.

引用

页数：20

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