1) strongly stationary
强平稳
1.
Linear Empirical Bayes Estimation for Strongly Stationary Φ- mixing Dependent Sequence and Its Application;
强平稳Φ－混合序列下的线性经验Bayes估计及应用
2.
In this paper,the empirical likelihood ratio confidence regions under strongly stationaryρ-mixing dependent samples are discussed,which generalizes Owen s(1988,1990)results for independent and identical distribution(i.
讨论了强平稳ρ混合样本的经验似然比置信区间,推广了Owen(1988,1990)在独立同分布情况下的结果,指出了相依情况时经验似然比置信区间的不足并进行了合理的改进。
3.
In this paper,we extend the conditionθ_0=EH(X,μ) to the equation of EH(X,θ_0,μ)=0 and,under the strongly stationary -mixing random sample,discuss empirical likelihood ratio confi- dence regions with a nuisance parameter.
本文将条件θ_0=EH(X,μ)推广到更一般的估计方程EH(X,θ_0,μ)=0,并且在样本为强平稳φ混合序列情形下讨论带有讨厌参数的经验似然比置信区域。
2) strong stationary
强平稳
1.
It is proved that these random variables are strong stationary and α- mixing random sequences, and these sequences obey the central limit theorem.
建立了“停走”生成器输出序列的概率模型 ,讨论了由这类序列构成的随机变量序列的概率分布、独立性、数学期望和方差等概率性质 ,在得到此类随机变量序列是强平稳的和 α-混合的这一结论的基础上证明了它们服从中心极限定
2.
Empirical likelihood estimator is discussed about parameter and distribution function under strong stationary m dependent samples.
在强平稳m 相依样本下讨论一般参数和分布函数的经验似然估计的求法及性质,推广了Qin and Lawless 在独立同分布情况下的结
3) strong stationary solution
强平稳解
4) strong stationary clutter
强平稳杂波
1.
We consider the problem of extracting the HRR features of moving targets with very closely spaced scatters in the presence of strong stationary clutter.
为了提取具有强平稳杂波背景和空间距离很近的散射体环境下运动目标的高距离分辨率特征,文中首先建立了强平稳杂波环境下运动目标的数学模型,采用基于松弛算法的非线性最小二乘算法估计了目标特征与杂波;然后对该算法进行了仿真实验,用最小均方误差与克莱美-罗界进行比较验证了该算法的优越性。
5) Stationary strongly mixing sequence
平稳强混合序列
6) strongly stationary NA Sequences
强平稳NA序列
补充资料：椐椐强强
1.相随貌。
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