检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]西北工业大学,西安710072
出 处:《弹箭与制导学报》2008年第6期250-252,共3页Journal of Projectiles,Rockets,Missiles and Guidance
基 金:国家自然科学基金(60574034);陕西省自然科学基金(2005A17)资助
摘 要:首先在X1,X2,…,Xn独立同分布(iidF)的情况下,给出了分位点过程n1/2{Fn-1(g)-F-1(g)}分布的随机加权估计;其次证明了n1/2{Fn-1(g)-F-1(g)}的随机加权逼近的相合性;最后将随机加权估计应用于多传感器数据融合中。仿真结果表明:文中提出的随机加权估计优于文献[4]所给出的Bootstrap逼近,提高了估计的精度。The probability distribution of independent and identically distributed (i. i. d) random variables was estimated by random weighting method. The consistency of random weighting approximation on the distribution of n^1/2{Fn^-1(g)-F^-1(g)} was studied. Under the condition of random variables series being NA associated sample, sample mean's approximation problem was discussed. Negative associated sample between strongly stationary and independent classes was defined. The sample was divided into k classes and the weight 1/k was given to the k jackknifed virtual values Y; (i = 1 ,…, k) of Xn.Then the empirical distribution function can be obtained. The distribution of √n(Xn-μ) was simulated by the conditional distribution of √n(Yk^*-Xn), where independent sample Y1^*,…,Yk^* was sampled from empirical distribution function Fk^*. For the distribution of n1/2 {Fn^-1 (g) -F^-1 (g)}, the consistency of the random weighting approximation was proved.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.192