【摘 要】
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We study the problem of estimating the coefficients in linear ordinary differential equations (ODEs) with a diverging number of variables when the solutions
【机 构】
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Nanyang Technological University(Singapore)
【出 处】
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2009 International Conference on Financial Statistics and Fi
论文部分内容阅读
We study the problem of estimating the coefficients in linear ordinary differential equations (ODEs) with a diverging number of variables when the solutions are observed with noise.The solution trajectories are first smoothed with local polynomial regression and the coefficients are estimated with nonconcave penalty proposed by (Fan & Li 2001).Under some regularity and sparsity conditions,we show the procedure can correctly identifies nonzero coefficients with probability converging to one and the estimators for nonzero coefficients have the same asymptotic normal distribution as they would have when the zero coefficients are known and the same two-step procedure is used.
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