1) likelihood ratio functional
似然比泛函
2) The profile empirical likelihood ratio function
边际似然比函数
3) preference-ratio functional
偏比泛函
1.
In this paper, the preference-ratio measure relative to a pair of alternatives and the preference-ratio functional are introduced, respectively, for an individual and a group in group decision making.
本文引进群体决策的决策个体和决策群体关于供选方案对的偏比度,以及偏比泛函概念。
4) likelihood function
似然函数
1.
The likelihood function is given for family data.
利用子代信息减少亲代单体型的不确定性,构建家系数据的似然函数,把家系中的个体潜在的单体型看成缺失数据,采用EM迭代算法,给出了家系数据单体型频率的极大似然估计。
2.
Put forward the reason of introduce the state space model of the ARIMA process, through the express of its state space model and Kalman filter relation for forecast, discuss the likelihood function and fresh interest means which based on state space model, probe into exact forecast means of the state space model of the ARIMA process.
通过ARIMA过程的状态空间表示和用于预报的Kalman滤波关系式,讨论了在状态空间模型时的似然函数和新息方法求解,探讨了ARIMA过程的状态空间模型的精确预报方法。
3.
Formalae are established describing how the round-off and observational errors influence the reduced likelihood function.
似然函数的Ａｌｉ算法和新息算法用矩阵表示并给出误差分析。
5) Likelihood ratio
似然比
1.
Multi-dimensional correlation test based on the probability integral translation and likelihood ratio
基于概率积分变换与似然比的高维相关性检验
2.
Discrete calculation of signal to noise ratio and likelihood ratio are discussed in detail,and one practical algorithm for the digital implementation of RPPT Detector is presented.
文章提出了高分辨率雷达目标随机参量脉冲串检测器的数字实现方法;详细讨论了离散条件下信噪比与似然比的计算,给出了RPPT检测器数字实现的一种实用算法。
3.
By making use of the notion of likelihood ratio and the approach of Laplace trans- form,a class of strong limit theorems represented by inequalities which call the strong deviation theorems are obtained.
研究了相依连续型非负随机变量序列的极限性质,利用似然比的概念和Laplace变换方法得到了一类强偏差定理,即用不等式表示的一类强极限定理。
6) likelihood ratio order
似然比序
1.
This paper investigates the likelihood ratio order and the increasing convex (concave) order for exponential family of distributions.
主要讨论两个服从同一指数型分布族的随机变量x和y之间的似然比序,一般随机序和单增凸(凹)序,并得到了判别上述序成立的一些充分条件。
2.
In this paper, we investigate the likelihood ratio order, the usual stochastic order and he increasing convex (concave) order in Gamma family of distributions.
主要讨论两个服从Gamma分布Γ (α ,λ)的随机变量X和Y之间的似然比序 ,一般随机序和单增凸 (凹 )序 ,并得到了判别上述序成立的一些充分条件 。
3.
It is established the conditions to ensure the stochastic comparison of the Likelihood ratio order between the groups of random variables.
研究了两组随机变量列之间似然比序的随机比较 ,得到的结果推广了 Shaked 和 Shan-thikumar( 1 994)中的 Theorem1 。
补充资料：似然比检验
分子式：
CAS号：
性质：假设总体X是连续型的，其密度是p(x)，则x1，x2，…，xn，的联合密度为g(x1，x2,…,xn)= p(x1)。关于样本的密度函数g(Xl，X2，…Xn；θ)有两个假设，H0:g(x1，x2，…xn；θ0)=p(xi, θ0)和H1:g(x1,x2，…xn；θ1)=p (xi；θ1)。统计量L(X1，X2，…，Xn)=称为假设H0对H1的检验问题的似然比。以似然比作统计量的检验，称作似然比检验。
CAS号：
性质：假设总体X是连续型的，其密度是p(x)，则x1，x2，…，xn，的联合密度为g(x1，x2,…,xn)= p(x1)。关于样本的密度函数g(Xl，X2，…Xn；θ)有两个假设，H0:g(x1，x2，…xn；θ0)=p(xi, θ0)和H1:g(x1,x2，…xn；θ1)=p (xi；θ1)。统计量L(X1，X2，…，Xn)=称为假设H0对H1的检验问题的似然比。以似然比作统计量的检验，称作似然比检验。
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