In this paper, we consider simulated minimum Hellinger distance (SMHD) inferences for count data. We consider grouped and ungrouped data and emphasize SMHD methods. The approaches extend the methods based on the deter...In this paper, we consider simulated minimum Hellinger distance (SMHD) inferences for count data. We consider grouped and ungrouped data and emphasize SMHD methods. The approaches extend the methods based on the deterministic version of Hellinger distance for count data. The methods are general, it only requires that random samples from the discrete parametric family can be drawn and can be used as alternative methods to estimation using probability generating function (pgf) or methods based matching moments. Whereas this paper focuses on count data, goodness of fit tests based on simulated Hellinger distance can also be applied for testing goodness of fit for continuous distributions when continuous observations are grouped into intervals like in the case of the traditional Pearson’s statistics. Asymptotic properties of the SMHD methods are studied and the methods appear to preserve the properties of having good efficiency and robustness of the deterministic version.展开更多
多支流交汇时各支流年最大流量是相互紧密关联的,若多支流年最大流量相互遭遇,交汇处则易形成峰高、量大的流域性大洪水.因此准确计算交汇处,尤其是缺乏实测资料地区的多支流交汇处年最大流量对判断洪水遭遇具有重要的实际意义,也是目...多支流交汇时各支流年最大流量是相互紧密关联的,若多支流年最大流量相互遭遇,交汇处则易形成峰高、量大的流域性大洪水.因此准确计算交汇处,尤其是缺乏实测资料地区的多支流交汇处年最大流量对判断洪水遭遇具有重要的实际意义,也是目前研究的难点.针对该问题,本文探索了多支流交汇的情况,构建了基于条件混合三维Copula函数的3支流年最大流量联合分布,联合蒙特卡洛方法模拟预测了干流年最大流量,并以美国亚利桑那州White River、Black River和Carrizo Creek 3条支流交汇为例开展了应用研究.结果发现,条件混合三维Copula模型得到的洪水频率与实际情况一致,说明该方法模拟3支流交汇处干流流量预测值是有效的,能够为多支流洪水遭遇分析计算提供新途径.展开更多
In this paper, we propose a robust mixture regression model based on the skew scale mixtures of normal distributions (RMR-SSMN) which can accommodate asymmetric, heavy-tailed and contaminated data better. For the vari...In this paper, we propose a robust mixture regression model based on the skew scale mixtures of normal distributions (RMR-SSMN) which can accommodate asymmetric, heavy-tailed and contaminated data better. For the variable selection problem, the penalized likelihood approach with a new combined penalty function which balances the SCAD and l<sub>2</sub> penalty is proposed. The adjusted EM algorithm is presented to get parameter estimates of RMR-SSMN models at a faster convergence rate. As simulations show, our mixture models are more robust than general FMR models and the new combined penalty function outperforms SCAD for variable selection. Finally, the proposed methodology and algorithm are applied to a real data set and achieve reasonable results.展开更多
假定随机误差分布来自具有重尾特征的scale mixtures of normal分布族,运用贝叶斯方法研究了函数型线性回归模型的稳健性估计,其中模型的响应变量为标量,解释变量为函数型变量.数值模拟结果表明:当响应变量的观测数据存在离群值时,建立...假定随机误差分布来自具有重尾特征的scale mixtures of normal分布族,运用贝叶斯方法研究了函数型线性回归模型的稳健性估计,其中模型的响应变量为标量,解释变量为函数型变量.数值模拟结果表明:当响应变量的观测数据存在离群值时,建立的方法得到的模型参数的估计,要优于正态分布假定下的模型参数的估计.展开更多
文摘In this paper, we consider simulated minimum Hellinger distance (SMHD) inferences for count data. We consider grouped and ungrouped data and emphasize SMHD methods. The approaches extend the methods based on the deterministic version of Hellinger distance for count data. The methods are general, it only requires that random samples from the discrete parametric family can be drawn and can be used as alternative methods to estimation using probability generating function (pgf) or methods based matching moments. Whereas this paper focuses on count data, goodness of fit tests based on simulated Hellinger distance can also be applied for testing goodness of fit for continuous distributions when continuous observations are grouped into intervals like in the case of the traditional Pearson’s statistics. Asymptotic properties of the SMHD methods are studied and the methods appear to preserve the properties of having good efficiency and robustness of the deterministic version.
文摘多支流交汇时各支流年最大流量是相互紧密关联的,若多支流年最大流量相互遭遇,交汇处则易形成峰高、量大的流域性大洪水.因此准确计算交汇处,尤其是缺乏实测资料地区的多支流交汇处年最大流量对判断洪水遭遇具有重要的实际意义,也是目前研究的难点.针对该问题,本文探索了多支流交汇的情况,构建了基于条件混合三维Copula函数的3支流年最大流量联合分布,联合蒙特卡洛方法模拟预测了干流年最大流量,并以美国亚利桑那州White River、Black River和Carrizo Creek 3条支流交汇为例开展了应用研究.结果发现,条件混合三维Copula模型得到的洪水频率与实际情况一致,说明该方法模拟3支流交汇处干流流量预测值是有效的,能够为多支流洪水遭遇分析计算提供新途径.
文摘In this paper, we propose a robust mixture regression model based on the skew scale mixtures of normal distributions (RMR-SSMN) which can accommodate asymmetric, heavy-tailed and contaminated data better. For the variable selection problem, the penalized likelihood approach with a new combined penalty function which balances the SCAD and l<sub>2</sub> penalty is proposed. The adjusted EM algorithm is presented to get parameter estimates of RMR-SSMN models at a faster convergence rate. As simulations show, our mixture models are more robust than general FMR models and the new combined penalty function outperforms SCAD for variable selection. Finally, the proposed methodology and algorithm are applied to a real data set and achieve reasonable results.
文摘假定随机误差分布来自具有重尾特征的scale mixtures of normal分布族,运用贝叶斯方法研究了函数型线性回归模型的稳健性估计,其中模型的响应变量为标量,解释变量为函数型变量.数值模拟结果表明:当响应变量的观测数据存在离群值时,建立的方法得到的模型参数的估计,要优于正态分布假定下的模型参数的估计.
