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LOCAL POLYNOMIAL DOUBLE-SMOOTHING ESTIMATION OF A CONDITIONAL DISTRIBUTION FUNCTION WITH DEPENDENT
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作者 Mimi Hong Xianzhu Xiong 《Annals of Applied Mathematics》 2017年第4期364-378,共15页
Based on the idea of local polynomial double-smoother, we propose an estimator of a conditional cumulative distribution function with dependent and left-truncated data. It is assumed that the observations form a stati... Based on the idea of local polynomial double-smoother, we propose an estimator of a conditional cumulative distribution function with dependent and left-truncated data. It is assumed that the observations form a stationary a-mixing sequence. Asymptotic normality of the estimator is established. The finite sample behavior of the estimator is investigated via simulations. 展开更多
关键词 local polynomial double-smoother conditional cumulative distribution function left-truncated data a-mixing asymototic normality
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Joint probability distribution of winds and waves from wave simulation of 20 years (1989-2008) in Bohai Bay 被引量:10
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作者 Xiao-chen YANG Qing-he ZHANG 《Water Science and Engineering》 EI CAS CSCD 2013年第3期296-307,共12页
The joint probability distribution of wind speed and significant wave height in the Bohai Bay was investigated by comparing the Gurnbel logistic model, the Gumbel-Hougaard (GH) copula function, and the Clayton copul... The joint probability distribution of wind speed and significant wave height in the Bohai Bay was investigated by comparing the Gurnbel logistic model, the Gumbel-Hougaard (GH) copula function, and the Clayton copula function. Twenty years of wind data from 1989 to 2008 were collected from the European Centre for Medium-Range Weather Forecasts (ECMWF) database and the blended wind data of the Quick Scatterometer (QSCAT) satellite data set and re-analysis data from the United States National Centers for Environmental Prediction (NCEP). Several typhoons were taken into account and merged with the background wind fields from the ECMWF or QSCAT/NCEP database. The 20-year data of significant wave height were calculated with the unstructured-grid version of the third-generation wind wave model Simulating WAves Nearshore (SWAN) under extreme wind process conditions. The Gumbel distribution was used for univariate and marginal distributions. The distribution parameters were estimated with the method of L-moments. Based on the marginal distributions, the joint probability distributions, the associated return periods, and the conditional probability distributions were obtained. The GH copula function was found to be optimal according to the ordinary least squares (OLS) test. The results show that wind waves are the prevailing type of wave in the Bohai Bay. 展开更多
关键词 wind speed wave simulation joint probability distribution copula function conditional probability distribution
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