unbiased conditions 中文意思是什麼
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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。 -
This paper studies mainly the theories of the semi - parametric regression model : ( 1 ) under proper conditions, using random weighted way to the estimator of the error density f ( x ) of the semi - parametric regression model, this paper proved the strong and weak consistent and the asymptotic unbiased property of the weighted kernel estimation fn1 ( x ) of the f ( x )
本文對半參數回歸模型：主要做了以下三個方面的理論研究： （ 1 ）將隨機加權法應用到半參數回歸模型的誤差密度f （ x ）的估計當中去，在適當的條件下，證明了誤差密度的加權核估計（ ? ） _ （ n1 ） （ x ）的強相合性、弱相合性及漸近無偏性。 -
As a result, we are not only unable to obtain the optimal prediction in general cases but incapable of finding the necessary and sufficient conditions as well. considering linear and o - linear predictable variables, the author investigates optimal prediction problems by the trace of matrix. a few necessary conditions are derived and accordingly optimal linear and optimal o - linear unbiased predictors, which are unique with probabitity one, are obtained respectively by the author
對於一類線性可預測變量和-線性可預測變量，作者在矩陣跡意義下研究了一般增長曲線模型中最優預測問題，找到了其存在最優預測的幾個必要條件，並在給定的條件下分別得到了最優線性無偏預測和最優-線性無偏預測，而且還證明了它們在幾乎處處意義下的唯一性
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