国家自然科学基金(10801118)

作品数：3被引量：4H指数：1
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Estimation for nearly unit root processes with GARCH errors被引量：4
《Applied Mathematics(A Journal of Chinese Universities)》2010年第3期297-306,共10页YUAN Yu-ze ZHANG Rong-mao Department of Mathematics, Zhejiang University, Hangzhou 310027, China 
Supported by the National Natural Science Foundation of China(10801118);Specialized Research Fund for the Doctor Program of Higher Education(200803351094)
In this paper the limiting distribution of the least square estimate for the autoregressive coefficient of a nearly unit root model with GARCH errors is derived. Since the limiting distribution depends on the unknown ...
关键词：Nearly unit root GARCH error least square estimation Ornstein-Uhlenbeck process empirical likelihood. 
A Functional LIL for Integrated α Stable Process
《Acta Mathematica Sinica,English Series》2010年第2期393-404,共12页Rong Mao ZHANG Zheng Yan LIN 
Supported by National Natural Science Foundation of China (Grant Nos. 10131040, 10371109 and 10801118)
Let {X（t）,t ∈ R＋} be an integrated α stable process. In this paper, a functional law of the iterated logarithm （LIL） is derived via estimating the small ball probability of X. As a corollary,, the classical C...
关键词：integrated α stable process functional law of the integrated logarithm small ball probability weighted occupation measure 
Asymptotic distributions of non-central studentized statistics
《Science China Mathematics》2009年第6期1262-1284,共23页SHAO QiMan ZHANG RongMao 
supported in part by Hong Kong UST (Grant No. DAG05/06.SC);Hong Kong RGC CERG(Grant No. 602206);supported by National Natural Science Foundation (Grant No.10801118);the PhD Programs Foundation of the Ministry of Education of China (Grant No. 200803351094)
Let X 1, ..., X n be independent and identically distributed random variables and W n = W n (X 1, ..., X n ) be an estimator of parameter ?. Denote T n = (W n ? ? 0)/s n , where s n 2 is a variance estimator of W n . ...
关键词：non-central studentized statistics studentized U-statistics studentized L-statistics limiting distributions power of tests 62E20 62F05 60F05 
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