Ӧ�ø���ͳ�� 2013, 29(6) 655-665 DOI:      ISSN: 1001-4268 CN: 31-1256

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Nonparametric Regression Method for Growth Curve Model
Gao Caiwen, Gan Hualai
School of Mathematics and Computer Science, Shanxi Datong University; School of Finance and Statistics, East China Normal University

In the research it is frequently assumed
that the growth curve is a polynomial in time. In practice,
researchers mainly use higher-order polynomials to obtain more
precise estimates. But this method has many defects, such as the
model can be easily affected by outliers and the polynomial
hypothesis may be much strong in practice. So in this paper we first
proposed nonparametric approach, local polynomial, instead of
parametric method for estimation in growth curve model. We give the
nonparametric growth curve model, and its nonparametric estimation.
Then discuss the large sample character of local polynomial
estimate. The ideal theoretical choice of a local bandwidth is also
discussed in detail in this paper. Finally, through the simulation
study, from the fitting curve and average square error box plot we
can clearly see that the performance of nonparametric approach is
much better than parametric technique.

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