CHINESE JOURNAL OF APPLIED PROBABILITY AND STATIST 2013, 29(4) 348-362 DOI:      ISSN: 1001-4268 CN: 31-1256

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The Strong Mixing Data-Based Semiparametric Smooth Transition Regression Model

Wang Chengyong, Ai Chunrong

School of Mathematics,Computer Science, Hubei University of Arts and Science; School of Statistics,Management,Shanghai University of Finance and Economics

Abstract��

In this paper, we generalize the
semiparametric smooth transition regression model proposed by Wang
(2012a), to adapt for the strictly stationary strong mixing data and
strong mixing data with deterministic trends. The unknown bounded
smooth function embedded in the smooth transition function is
estimated by series estimator, the consistency and asymptotic
normality properties of estimators are proved employing nonlinear
least square regression theory and series estimator approach.
Variance matrix estimation and hypothesis testing problems are also
discussed based on estimated standard errors. The new model is then
used to study the annually inflation rates of China.

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Corresponding Authors: Wang Chengyong
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