样本均值

求解带约束随机规划问题的光滑化样本均值逼近方法

Smooth Sample Average Approximation Method for Nonsmooth Stochastic Programming with Constraints

一种样本均值和标准差值的电算化算法

A computer algorithm on sample average value and st and ard deviation

计算近似积分的样本均值MonteCarlo方法

The sample mean Monte Carlo method for approximate integral using measure theory

NA样本均值的Bootstrap逼近

Bootstrap approximate of NA sample mean-value

样本均值Bootstrap逼近的收敛速度

Convergence rate of the bootstrap approximation for the sample mean

并利用BP算法得到输出与样本均值之间的关系图，从系统输出值的归属区间判断初级指挥员素质的高低。

The BP algorithm was also adopted to get the relation image between output and average value of sample . The attribution regions of system output value were used to judge the diathesis level of primary commanders .

首先用MCMC方法估计得到模型参数值，克服了传统的直接用样本均值和样本方差进行参数估计值的不足，与市场实际更吻合；

First , we use MCMC method , which covers the shortage of conventional parameter estimation methods , to estimate model 's parameters and get more appropriate parameter evaluations .

首先，综合运用样本均值T检验、中值Wilcoxon检验、相关分析、回归分析等多种方法对研究假设进行实证检验。

First of all , I make comprehensive use of T test sample mean , median Wilcoxon test , correlation analysis , regression analysis and other methods to verify hypotheses .

本文讨论了标准化样本均值分布的光滑化Bootstrap估计的相合性，并给出了这种逼近的收敛速度。

In this paper , the consistency of the smooth Bootstrap estimation for the distribution of the standard sample mean is discussed and the convergence rate of the smooth Bootstrap approximation of the distribution of the sample mean is given .

本文给出了样本均值随机加权估计的条件分布以概率（几乎处处）收敛到正态分布的充要条件为X1属于正态吸收域D（2）（E（X~21）＜∞）；

In this paper , we show the necessary and sufficient condition for convergence in probability ( a.s. ) of the distribution function of a random weighting mean is that the sampling comes from the domain of attraction of normal distribution ( EX ~ 2_1 < ∞) .

从Xbar-R控制图的假设检验问题出发，研究了t时刻样本均值（Xbar）和极差（R）处于控制限内不同位置时，Xbar-R控制图假设检验的第二类错误（β风险）问题。

Based on the hypothesis of Xbar-R control chart , the type II error (β risk ) of Xbar-R control chart was studied when the Sample 's mean at time t lied in different positions between upper control limit and lower control limit of Xbar-R chart .

截断情况下独立随机变量样本均值和方差的近似分布

And variance of a sample of independent variables with censored data

标准化样本均值分布的随机加权逼近&多维情形

Random weighting approximation for the distribution of standardized sample mean-multi-dimensional case

数据有所变动的样本均值及方差的简易求法

Simple Way to Get Average and Variance When Datum of Samples Change

一元有限总体样本均值分布的随机加权逼近

Random Weighting Approximation for Distribution of Sample Mean in One-dimensional Finite Population

通过对样本均值的比较，分别得出各维度在员工和管理者心目中的重要性排序。

The comparison of means to evaluate the sequence of every dimension .

m相依样本均值随机加权估计的渐近性质

The Asymptotic Behavior of the Random Weighting Estimate for m-dependent Sample Mean

介绍有序样本均值聚类分析方法。

The fundamental of ordered sample mean classification method is Concisely explained .

样本均值函数的期望及收敛速度

The expectation value of the function of sample averange and its convergence rate

比较两组样本均值的随机加权法

A Random Weighting Method for the Comparison of the Means of Two Independent Samples

小子样样本均值区间估计方法及其比较

Interval Estimation Methods of the Mean in Small Sample Situation and the Results ' Comparison

关于样本均值的抽样分布能否作正态近似的探讨集平均；统计平均值；系综平均值；总体均值

The Argument whether Sampling Distribution of Expectation of Samples Approximately Obey Normal Distribution ; ensemble average

作者利用影响函数，讨论了样本均值和中位数的抗差能力。

In this article , robustness of mean and median is discussed by using influence function .

文中提出的估计与传统的样本均值相比较有较高的精度。

The suggested estimators have usually higher precision compared with the commonly used systematic sample mean .

在简单随机抽样中，样本均值是总体均值的无偏估计。

In a simple random sampling , the sample mean is an unbiased estimate of the population mean .

该方法通过重抽样获得样本均值的估计，并通过该估计利用分位数插值的方法构造了均值向量的边际等尾联合置信区间。

By the bootstrap estimation of mean vector , we use the percentile interpolation to construct simultaneous confidence intervals .

对于样本均值估计总体均值，给出了基于误差限制的样本容量的计算式。

The calculation formulas of sample size based on the error limitation are given for estimation of population mean .

处于磁体中心层的图像信噪比样本均值大于其它层面的图像信噪比样本均值（t检验P<0.05）。

The swatch mean value of images SNR on magnet isocenter was greater than others ( TTEST P < 0.05 ) .

对于样本均值的误差分布，用随机加权法给出了精度为的逼近分布。

Using the random weighting method , for the distribution of sample mean , its approximate distribution which precision reaches is obtained .

我们有几种不同的方式去定义这个概念，萚鲇谖颐侵傅氖？样本均值还是总体均值。

We can define it in a couple of different ways depending on whether we 're talking about sample mean or population mean .