【摘 要】
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We are interested in nonparametric estimation for the data contaminated with heteroscedastic measurement errors.Challenges of estimation problems arise when
【机 构】
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Cleveland Clinic, USA
【出 处】
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IMS-China International Conference on Statistics and Probabi
论文部分内容阅读
We are interested in nonparametric estimation for the data contaminated with heteroscedastic measurement errors.Challenges of estimation problems arise when errors are heteroscedastic where we literally have only one observation for each error distribution.Two estimation procedures are studied here: SIMEX-type estimation and a new procedure named as Shannon Weighted Average Procedure (SWAP).The resulting estimators are stable and easy to compute-there are no Fourier trans formations needed in the calculation.The estimators have faster convergence rates thanthose of Fourier type estimators.Some simulation studies and data applications will also be presented.
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