Kernel Density-Based Linear Regression Estimate
نویسندگان
چکیده
منابع مشابه
Kernel Density Based Linear Regression Estimate
For linear regression models with non-normally distributed errors, the least squares estimate (LSE) will lose some efficiency compared to the maximum likelihood estimate (MLE). In this article, we propose a kernel density based regression estimate (KDRE) that is adaptive to the unknown error distribution. The key idea is to approximate the likelihood function by using a nonparametric kernel den...
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ژورنال
عنوان ژورنال: Communications in Statistics - Theory and Methods
سال: 2013
ISSN: 0361-0926,1532-415X
DOI: 10.1080/03610926.2011.650269