Bai Mei-li
Abstract
Considering semiparametric regression model with a linear process errors Y_(ni) =β·t_(ni)+g(x_(ni))+e_(ni), 1≤i≤n,we use the least squares and usual weighted method to define the estimatesβ_n and g_n forβand g and obtain their r-th mean consistency and asymptotic normality for g_n under suitable conditions.
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Considering semiparametric regression model with a linear process errors Y_(ni) =β·t_(ni)+g(x_(ni))+e_(ni), 1≤i≤n,we use the least squares and usual weighted method to define the estimatesβ_n and g_n forβand g and obtain their r-th mean consistency and asymptotic normality for g_n under suitable conditions.
Key concepts: Mathematics, Consistency (knowledge bases), Semiparametric regression, Asymptotic distribution, Linear regression, Semiparametric model, Statistics, Regression