Berry–Esseen bound of wavelet estimators in heteroscedastic regression model with random errors
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DOI: 10.1080/00207160.2018.1487958
Abstract: ABSTRACT For the heteroscedastic regression model , where , are known to be nonrandom design points, and are defined on the closed interval [0,1]. When is known, we investigate the Berry–Esseen type bounds for wavelet… read more here.
Keywords: random errors; berry esseen; regression model; heteroscedastic regression ... See more keywords
Wavelet estimators for the derivatives of the density function from data contaminated with heteroscedastic measurement errors
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DOI: 10.1080/03610926.2016.1148735
Abstract: ABSTRACT Measurement errors occur in many real data applications. In this paper, the linear and the non linear wavelet estimators of the derivatives of the density function are constructed in the case of data contaminated… read more here.
Keywords: estimators derivatives; measurement errors; data contaminated; density function ... See more keywords
Asymptotic properties of wavelet estimators in heteroscedastic semiparametric model based on negatively associated innovations
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Inequalities and Applications"
DOI: 10.1186/s13660-019-2267-4
Abstract: Consider the heteroscedastic semiparametric regression model yi=xiβ+g(ti)+εi$y_{i}=x_{i}\beta+g(t_{i})+\varepsilon_{i}$, i=1,2,…,n$i=1, 2, \ldots, n$, where β is an unknown slope parameter, εi=σiei$\varepsilon_{i}=\sigma_{i}e_{i}$, σi2=f(ui)$\sigma^{2}_{i}=f(u_{i})$, (xi,ti,ui)$(x_{i},t_{i},u_{i})$ are nonrandom design points, yi$y_{i}$ are the response variables, f and g are unknown… read more here.
Keywords: heteroscedastic semiparametric; properties wavelet; asymptotic properties; model ... See more keywords