unbiased mean 中文意思是什麼
unbiased mean
解釋
無偏平均數-
We make the following assumption for when 2 is positive definite matrix, different estimators about matrix of regression coefficients and inefficiency of least squares estimate have been discussed in many documents. considered 2 is nonnegative definite matrix, this thesis derives best linear unbiased estimate of parameter matrix b and estimable parameter function kbl under the meaning of matrix nonnegative definite and the property of maximum probability of blue is investigated. next, we discuss some necessary and sufficient conditions of the equality of the lse and blue, then we derive the estimation of the deviation bet - ween the least squares and the best linear unbias estimators of the mean matrix, meanwhile a relative efficiency of lse ofb is proposed and its bound is given
當0時，眾多文獻討論了回歸系數陣的各種估計及lse的有效性，本文考慮了當0的情形，給出了回歸系數陣b及其可估參數函數kbl的在矩陣非負定意義下的最優估計（ blue ） ，研究了它的一個最大概率性質，並且討論了最小二乘估計成為最佳線性無偏估計的充分必要條件，在此基礎上給出了均值矩陣的最小二乘估計與blue的偏差估計，定義了lse相對于blue的一個相對效率，並給出了它的界。 -
In the sense of mean squares, maximum likelihood estimator, best linear unbiased estimator, taest linear invariant estimator, and good linear estimator are contracted. fourth, proposed and researched the reliability analysis method under the zero - failure data and doof data. based on the part beta distribution as the prior distribution of failure probability p, = p ( t < r, }, hierarchical bayesian estimate method was discussed, obtain the reliability analysis method under the zero - failure data and the doof data
第四，提出並研究了無失效數據類型和doof數據類型下電連接器的可靠性分析方法，提出了以不完全beta分佈為一級先驗分佈，超參數為[ 0 ， 1 ]上的均勻分佈作為失效概率先驗分佈的多層bayes方法，結合加權最小二乘法解決了產品在無失效數據和doof數據下的可靠性分析問題。 -
Abstract : the generalized shrunken prediction of finite population is introduced, using generalized shrunken least squares estimator of linear regression models. with respect to prediction mean squared error, a necessary and sufficient condition for superiority of a generalized shrunken prediction over the best linear unbiased prediction is obtained. in the case of linear combination of every unit index, a linear restricting prediction is introduced and then a necessary and sufficient condition for superiority of linear restricting prediction over the best linear unbiased prediction is devived
文摘:利用線性回歸模型的廣義壓縮最小二乘估計，引入了有限總體的廣義壓縮型預測，在預測均方誤差意義下，得到了廣義壓縮型預測優于最佳線性無偏預測的一個充分必要條件；在只能得到每個個體指標的線性組合時，引入了一種線性約束型預測，並得到了線性約束型預測優于最佳線性無偏預測的一個充分必要條件 -
Problem set 5 : shape of the limiting distribution for unbiased, subdiffusive ctrw ; mean escape time from a symmetric potential well, low temperature asymptotics
問題5 ：不偏的次ctrw極限公布的形狀；從對稱型勢位能逃脫平均時間，低溫盡近似。 -
Traditional research has put much effort on finding the unbiased and less - constricted parameters of mean - variance ( m - v ) portfolio theory. on one hand mean - variance is perfect in its mathematic sense
本論文主要目的是利用再抽樣方法改進傳統均值-方差模型，以使其得到更大的實際應用。
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