1) Taguchi loss functions
塔古奇损失函数
1.
Study of mechanism of evaluation and selection system of suppliers based on Taguchi loss functions and analytic hierarchy process
基于塔古奇损失函数和AHP法的供应商评选机制研究
2) loss function
损失函数
1.
Mis-acceptance and mis-rejection in product examination and analysis of quality loss function;
测量检验中误收、误废和质量损失函数的分析
2.
Research on stochastic facility layout problem based on loss function;
基于损失函数的随机设施布局优化分析
3.
Multi-output support vector regression with piecewise loss function;
具有多分段损失函数的多输出支持向量机回归
3) Lost function
损失函数
1.
The sample size in random sampling can then be determined through forming the lost function.
在随机抽样的前提下,应首先定性地分析样本容量确定的影响因素,然后对精度和费用这两个可以量化的因素进行定量分析,并通过构建损失函数达到确定随机抽样样本容量之目的。
4) Huber loss function
Huber损失函数
1.
Finiteness of the V γ dimension of the set of Huber loss function for regression is studied in a ball of radius R in an infinite dimension RKHS,and an upper bound of it is estimated.
研究了无限再生核希尔伯特空间 (RKHS)中半径为R的球内回归估计的Huber损失函数集Vγ 维的有限性 ,给出其Vγ 维的上界估计 ,从而保证此类回归机器的依概率一致收敛 ,使其具有较好的推广能
5) entropy loss function
熵损失函数
1.
Bayesian estimation of geometric distribution parameterunder entropy loss function;
熵损失函数下几何分布参数的Bayes估计
2.
In this paper,the formula of Expect Bayes estimation of the reliability under entropy loss function for geometric distribution have been given,when the prior distribution of the reliability is power distribution and βdistribution.
研究几何分布可靠度的先验分布分别为β分布和幂分布时,在熵损失函数下给出了可靠度的EB估计,并结合实际数据比较了两种先验分布下估计值的精度。
3.
This paper considers comparison of MINQUE and simple estimator of Σ in the mult-ivariate normal linear model Y-N(XB, Σ V) under the risk of entropy loss function and symmetry loss function criterion, where the design matrix X need not have full rank and the dispersion matrix V can be singular.
并证明了,在熵损失函数下,MINQUE估计总是优于简单估计。
6) LINEX loss function
LINEX损失函数
1.
Under Linex loss function L(θ,δ)=ec(δ-θ)-c(δ-θ)-1,c>0,It is proved that the unique Bayes estimator δB(x),the multilayer Bayes estimator δ^B(X) and the general form of the admissible estimator are δB(X)=-1cln E(e-cθ|X)=n+αcln(1+cλ+T),δ^B(X)=-1cln(∫c0∫10Kλα(λ+c+T)n+αdαdλ∫c0∫10Kλα(λ+T)n+αdαdλ) and Sln(1+cd+T) respectively for the scale parameter reciprocal of the Rayleigh distribution.
在Linex损失函数L(θ,δ)=ec(δ-θ)-c(δ-θ)-1,c>0下,给出Rayleigh分布的尺度参数倒数的唯一Bayes估计δB(X)=-1/clnE(e-cθ│X)=(n+α)/cln(1+c/(λ+T)),多层Byaes估计δ∧B(X)=-1/cln,和容许性估计的一般形式Sln(1+c/(d+T))。
2.
First, we obtain the empirical Bayesian estimator of the scale parameter for the double exponential distribution based on LINEX loss function and the convergence rate of the estimate.
首先利用非对称的LINEX损失函数对双指数分布族刻度参数进行了经验贝叶斯估计,并讨论了该估计的性质,给出了收敛速度。
补充资料:损失函数
损失函数
loss function
损失函数〔卜.云州地阅;uoTep‘柯田叫.a] 统计判定问题中,对于试验的每一种可能结局表示试验者损失(成本)的非负函数.设X是在样本空间任,刃,p,)(口‘。)中取值的随机变盘;D={心是根据X的实现关于参数a可以作出的一切可能判决的空间.在决策函数理论中,定义在OxD上的任一非负函数L称为损失函数.当参数的真值为e时(e‘O),损失函数L在任一点(a,d)任exD的值表示作出判决d(d〔D)所造成的损失.
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
参考词条