正态总体

  • 网络normal population
正态总体正态总体
  1. 正态总体方差几类估计量的比较

    Comparision the Some Estimators of the Normal Population Variance

  2. 数字高程模型中求趋势的一种方法&无偏最优求趋势法本文给出了求正态总体方差的一致最优化无偏检验的临界值的算法。

    Best Unbiased Estimator for Trend & A Method of Getting Trend of Digital Elevation Model This paper proposed an algorithm for finding critical value of normal population variance under unbiassed tests with uniform dominance .

  3. 关于非正态总体的工序能力指数Cp值计算的研究

    Research on computing the value of the work procedure ability index C_p

  4. 正态总体均值的假设检验及其在Excel中的实现

    Hypothesis Testing of Normal Population Mean and Its Application in Excel

  5. 正态总体均值的F检验法

    The Method of F-Test for the Hypothesis Testing of the Mean of the Normal Distribution

  6. 对于均值μ和方差σ2均未知的正态总体N(μ,σ2),其均值的序贯估计是一个重要的问题。

    For a normal populations μ with unknown mean σ 2 and variance N (μ,σ 2 ), estimation for the mean is an important question .

  7. 最佳渐近正规估计量渐进多元正态总体均值最紧致某处最优势检验秩集样本的应用渐变为最大(G)

    The most stringent somewhere most powerful one sided test of the asymptotic multivariate normal population mean & The application of the ranked set sample ;

  8. 对正态总体进行观测正常人正交导联心电图QRS波

    The Observation of to Normal Distribution of Population CORRECTED ORTHOGONAL ELECTROCARDIOGRAM IN NORMAL POPULATION

  9. 正态总体中线性可预测变量的Minimax预测

    Minimax predictor of linear predictable variable in normal populations

  10. 正态总体的Bayes判别模型与负点法在处理微量超差中的应用

    The application to the judgment model of normal population 's Bayes and negative point method to dealing with tiny super-difference

  11. 许多实际问题要求对多元正态总体np(μ,∑)的μ和∑进行统计推断。

    In a lot of backgrounds , we are required to give statistical inference of μ and Σ , which are parameters of multivariate normal population N_p (μ,Σ) .

  12. 本文应用正态总体的Bayes判别模型,解决了微量超差的两类判别问题,并完成了向负点法的转化工作。

    This article employs the judgment model of normal population 's Bayes to deal with two kinds of judgments of tiny super difference , and manages to transform into Negative point method .

  13. 证明了取自两个正态总体的两个简单随机子样X与Y当(X,Y)τ为正态随机向量时(特别,当两子样独立时)两子样方差仍相互独立。

    It has been proved that for two simple samples from two normal populations X and Y , if ( X , Y ) ' is normal ( specially , if X , Y are independent ) then two sample variances are independent .

  14. 本文证明了来自两个正态总体的两子样未必独立时,两子样方差仍相互独立,说明F检验法中要求两子样独立的条件是不必要的。

    In this paper , We prove that two Samples from two noral universes are not independent , but two sample variances are independent . Therefore , in the F - tests the condition that two samples are independent may be deleted .

  15. 本文利用尾部概率的估计导出了Pitman准则下一个估计优于另一估计的充分条件,并把它应用于正态总体方差估计的比较。

    A sufficient condition for the superiority of one estimator over another was established under the Pitman criterion by estimating the tail probability of a random variable . The estimators of the variance in the normal distribution case were compared as an example of the applications .

  16. 一类非正态总体的抽样检验方案

    A Kind of Measuring Sampling Plans of non - normal Totality

  17. 平衡损失下正态总体均值的序贯估计

    Sequential Estimation for the Mean of Normal Population Under Balanced Loss

  18. 非正态总体的估计和检验问题

    The Problem of Estimation or Hypothesis Tests for Non-normal Distribution

  19. 两正态总体方差比的优化置信区间

    Best Confidence Interval of Ratio of Two Normal Random Variables

  20. 正态总体样本协差阵正定性一新证明

    A New Proof of the Positive Definiteness on the Sample Covariance Matrix

  21. 子弹散布中心正态总体分布参数的融合估计

    Fusion Estimation of Normal Distribution Parameter of the Sub missile Dispersion Center

  22. 正态总体分解的算法与应用讨论

    A discussion on Algorithm and application for normal population decomposition

  23. 由此出发,本文作者曾在文中导出了非正态总体所服从的概率密度函数和概率分布函数,并给出了其相应的概率分布表。

    The associated probability density function and probability distribution function were deduced .

  24. 两个正态总体参数的线性关系的假设检验

    A Testing Hypothesis for two Normal Population Parameters in the Linear Relation

  25. 多维正态总体零均值的假设检验

    Testing of multi - dimensional normal population with mean zero

  26. 正态总体方差最短置信区间的研究

    Study on Minimum Length of Confidence Interval for Variance of Normal Distribution

  27. 正态总体均值方差的经验似然比置信区间估计

    Empirical Likelihood Ratio Confidence Interval Estimation for Normal Population Parameters

  28. 正态总体均期一致最优无偏检验

    The Uniformly Most Powerful Unbiased Test of the Normal Mean

  29. 并利用秩集样本进行了渐进多元正态总体均值的最紧致某处最优势检验。

    Then the ranked set sample has been used to do the test .

  30. 来自正态总体非独立样本的转换方法

    The Method of Transformation From Normal Population Non-independent Sample