regression estimator 中文意思是什麼

regression estimator 解釋
回歸估計量
  • regression : n. 1. 復歸，回歸。2. 退步，退化。3. 【天文學】退行。adj. -sive ,-sively adv.
  • estimator : n. 估計者；估計量。
  1. Abstract : since the multiple failures situation is not uncommon in the clinical medicine, we explore the use of proportional odds model to the multivariate interval - censored data. the approach is based on the conditional logistic regression, which prevents the complications in the existence of nuisance parameters. the estimation of parameters is obtained by the newton - raphson algorithm. the sandwith estimator for the covariance is made according to the situation where there is correlation in the score statistic. simulations are also presented to assess the accuracy of the procedure

    文摘:探索比例優勢模型在臨床醫學中常見的多結局區間截斷數據中的應用.用條件的邏輯回歸方法避免討厭參數的估計，用牛頓-拉普森演算法估計回歸系數，用"夾心方差"估計量作為參數方差的估計.通過隨機模型檢驗模型應用的有效性
  2. The regression estimator in cluster random sampling

    整群抽樣回歸估計量
  3. Weighted kernel estimator of nonparametric regression functions with censored data of sequences

    相依截尾數據非參數回歸函數加權核估計
  4. The essence of the above estimating methods is local estimator or local smoothing technique. in general, the non - parametric regression function is. well estimated by the above methods when the covariable x is one dimension

    這些方法本質上講都是局部估計或局部光滑，當回歸變量x為一維變量時，非參數回歸函數用這些方法一般都能得到很好的估計。
  5. Cumulative method in semiparametric regression model - nonparametric estimator base on wavelet smoothing

    非參數估計基於小波光滑
  6. 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。
  7. 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
  8. In the late 30 or 40 years, many scholars have a lot of studies on a seemingly unrelated regression ( sdr ) system with two linear regression models, and some important results are obtained : zellner ( 1962 ) put forward two - stage estimator ( tse ) ; based on zellner " s, lin chun - shi ( 1984 ) obtained the sufficient and necessary condition of two - stage estimator ; chen chang - hua ( 1986 ) discussed the tse and its optimalities without any condition for designed - matrix x ; ulteriorly, wang song - gui and van li - qing ( 1997 ) obtained an iteration sequence of estimator by using the covariance - improved approach ; liu jin - shan ( 1994 ), li wen and lin ju - gan ( 1997 ) generalized the covariance - improved estimator respectively

    半相依回歸系統是由兩個誤差項相關的線性回歸方程組成的系統。近三、四十年來，已有很多的學者對這類半相依回歸系統進行了大量的研究，作出了十分重要的成果： zellner （ 1962 ）提出了所謂兩步估計法；在其基礎上，林春士（ 1984 ）得出了兩步估計的充要條件，陳昌華（ 1986 ）討論了對設計矩陣不作任何要求的兩步估計及其優良性；進一步地，王松貴、嚴利清（ 1997 ）利用協方差改進法獲得了參數的一個迭代估計序列，劉金山（ 1994 ） ，李文、林舉干（ 1997 ）則分別對協方差改進估計進行了推廣。
  9. The admissible estimator of stochastic regression coefficients and parameters in stochastic effective linear model with constraints

    帶約束的隨機效應線性模型中的回歸系數和參數的可容許性估計
  10. But the multivariable nonparametric regression function could not be well estimated by the local estimator because there is o nly a little data in the local fields of the high dimension regression variable x. this phenomenon is said to be " the curse of dimension "

    但當回歸變量是多維向量時，由於x的局部鄰域包含很少的數據，用這些估計方法，很難估計出一般的多元非參數回歸函數，人們把這種現象稱為『維數禍根』 （ thecurseofdimension ） 。
  11. The basic idea of the estimate method is, firstly, based on the linear model yi = x ' i + ei, defining the least square estimator n of the linear model for the unkown parametric ; secondly, using the estimator n we " ve got to substitute for in the original semiparametric regression model yi = x ' i + g ( xi ) + ei and using the usual nonparametric weighted function method to define the estimator gn ( - ) for the unknown function g ( ) ; finally, defining the estimator 2 for the unknown variance of errors 2

    其估計方法的基本思路是先基於線性模型y _ i = x _ i + e _ i ，定義未知待估參數的估計即此線性模型的最小二乘估計（ ? ） _ n ；然後將所得估計（ ? ） _ n代入原半參數回歸模型中，用一般的非參數權函數方法定義未知函數g （ ? ）的估計（
  12. Chapter 5 is focused on the studies on the equivalent conditions for maximum value convergence of sums of independent random matrix sequences, and the sufficiency condition of the strong consistency of m estimator of regression parametric in linear model for negatively associate samples, thus enriching and strengthening the results of a series of papers

    第五章得到了獨立陣列和（含加權和）的最大值完全收斂的等價條件，從而豐富和強化了前人的一系列結果獲得了負相關樣本線性模型中回歸參數m估計是強相合的較弱的充分條件
  13. Based on wavelet analysis, wls is the best linear unbiased estimator of regression model parameters in the context of l / f noise

    基於小波技術的wls法是具有1 f噪聲的系統回歸模型參數的最佳線性無偏估計。
  14. Based on [ 4 ], the author adds a linear restriction r = r to this sur system, and discusses the estimator and the optimalities of unknown regression coefficient ft in the sur system under the linear restriction

    本文將在文獻[ 4 ]的基礎上，對此sur系統增加一線性約束r = r ，討論在此線性約束r = r下半相依回歸系統中未知回歸系數_ 1的估計及其優良性問題。
  15. Of unknown regression coefficient ft under the linear restriction r = r and its convergence, that is : 2. the optimalities of covariance - improved estimator sequence under three mde crlterions ; 3

    求出了在線性約束r = r下未知回歸系數_ 1的協方差改進估計序列，及此序列的收斂性： 2
  16. For the regression estimation when the auxiliary variate is correlated with the disturbance, the bias and mean square error ( mse ) of the regression estimator are obtained, and the estimator of the mse is presented

    摘要討論了輔助變量與擾動項相關條件下的回歸估計，給出了在這種條件下回歸估計量的偏差和均方誤差以及均方誤差的估計。
  17. All kinds of the methods are proposed to estimate the nonparametric regression function, such as the kernel method, the local polynomial estimators, the smoothing spline, the series estimators ( b - spline estimator. fourier series estimator, wavelet series estimator )

    對于非參數回歸人們提出了許多估計方法，如核估計，局部多項式估計，光滑樣條估計，級數估計（傅里葉級數估計，小波級數估計）等。
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