最小二乘估計 的英文怎麼說

中文拼音 [zuìxiǎoèrchénggūjì]
最小二乘估計 英文
least square estimation
  • 最 : 副詞（表示某種屬性超過所有同類的人或事物） most; best; worst; first; very; least; above all; -est
  • 小 : Ⅰ形容詞1 （體積、面積、數量、強度等不大） small; little; petty; minor 2 （年紀小的; 年幼的） youn...
  • 二 : Ⅰ數詞（一加一后所得） two Ⅱ形容詞（兩樣） different
  • 估 : 估構詞成分。
  • 計 : Ⅰ動詞1 （計算） count; compute; calculate; number 2 （設想; 打算） plan; plot Ⅱ名詞1 （測量或計算...
  • 估計 : estimate; evaluate; take stock of; size up; calculate; appraise; reckon; estimation; forecast
  1. Then discusses its properties, such as biased property, relative efficiency of generalized variance and superiority comparisons between generalized ridge estimation and generalized least squares estimation. shows iterative algorithm based on the mean dispersion error

    該估計雖然具有偏崎，但其估計精度具有良好的性質，如：有偏性、方差一致最優性、相對于廣義最小二乘估計的廣義方差效率、 mde ? ?有效性等。
  2. Thus proposes an alternative method for the research of superiority of two predictors based on the biased estimation. in the light of the approximate multicollinearity of matrix, distance for principal components estimation ( namely distance ) is put forward

    針對設計矩陣的多重共線性問題，為了改進基於最小二乘估計的統計診斷量cook距離，提出了基於massy主成分下的cook距離（ mpcc距離） 。
  3. 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。
  4. The choice of smoothing parameter can be automatically obtained by using generalized cross - validation function

    自編程序進行計算，得到了回歸參數向量和樣條函數的補償最小二乘估計。
  5. Under a certain conditions on variance matrix invertibility, we show that the optimally weighted ls estimate outperforms the linear minimum variance estimate provided that they have the same priori information

    因此，我們討論了在相同已知信息的情況下，即最優加權最小二乘估計也利用有關被估參數的先驗信息時，二者的估計性能。
  6. For a general linear model ( input matrix is deterministic ), under a certain conditions on variance matrix invertibility, the two estimates can be identical provided that they have the same priori information on the parameter under estimation. even if the above information is unknown only for the optimally weighted ls estimate, the sufficient condition and necessary condition, under which the two estimates are identical, is derived. more significantly, we know how to design input of the linear system to make the performance of the optimally weighted ls estimation identical to that of the linear minimum variance estimation in case of being lack of prior information

    在一般線性模型（即輸入矩陣為確定性）下，當兩種估計都利用有關被估參數的先驗信息時，二者在方差陣可逆的一定條件下可達到一致；當最優加權最小二乘估計不利用此先驗信息時，存在二者一致的充分條件和必要條件，進而找到一種設計輸入矩陣的方法，使得在先驗信息缺乏的條件下，仍可利用最優加權最小二乘估計達到與線性最小方差估計一樣優越的估計性能。
  7. In this thesis, based on item response theory, a number of ways to estimate the latent trait and item parameters were introduced and their advantages and disadvantages were analyzed ; what is more, empirical logistic regression and two parameters logistic model ( 2plm ) are combined to set up a linear model by logit - mapping and a new parameter - estimation method is proposed

    新方法將經驗logistic回歸用於兩參數logistic模型的參數估計，使用logit變換建立線性模型，利用線性模型的最小二乘估計得到第j個項目的項目參數向量_ j = （ _ j ， _ j ）的兩步估計由於x _ j含有未知的討厭參數，的理論值也和有關，我們結合上式的結果對進行再估計。
  8. A new relative efficiency of the least squares estimator in growth curve model

    生長曲線模型中最小二乘估計的一種新的相對效率
  9. The least square estimate of covariance matrix in the restricted growth curve model

    有約束的生長曲線模型中協差陣的最小二乘估計
  10. Admissibility of generalized least square estimator on the unknown parameter matrix in the extensive growth curve

    推廣的生長曲線模型中未知參數矩陣的廣義最小二乘估計的可容許性
  11. Then we give the necessary and sufficient condition under which the optimally weighted ls estimate is identical to thu conditional mean of the parameter given input and observation, i. e., the optimally weighted ls estimate could be optimal nonlinear estimate in the minimum variance sense

    在方差陣可逆的條件下，我們發現最優加權最小二乘估計優于線性最小方差估計，進而得到了其與最小方差估計（即條件均值估計）等價的充要條件。
  12. Asymptotic normality of pseudo - ls estimator of error variance in partly linear autoregressive models

    部分線性自回歸模型中誤差方差偽最小二乘估計的漸近正態性
  13. Based on the least squares and biased estimation especially ridge estimation, a new estimation, that is, generalized ridge estimation is put forward through studies on restriction of the parameter. model ' s prediction being considered, comparison of superiority of optimal and classical predictions with respect to the ridge estimation is showed. regression diagnoses especially distance for principal components estimation is discussed

    論文基於最小二乘估計及有偏估計特別是嶺估計，對參數的約束條件做了進一步研究，並提出一種新型估計即廣義嶺型估計；對模型的點預測問題進行深入探索，得出一種基於嶺估計關于經典預測和最優預測的最優性判別條件；也對回歸診斷特別是基於主成分估計的距離進行了深入探討。
  14. This paper consists of two parts : in the first part, we will discuss the prob - lem of the pth - mean, complete consistency for the estimators of a nonparamet - ric and linear model with l ~ p - mixingale errors ; in the second part, we will dis - cuss the problem of the rth - mean 、 complete consistency for the estimators of themodels above with weak stationary linear process errors and the uniformly mean consistency. to the nonparametric model y _ ni = g ( x _ ni ) + _ ni, 1 i n, let g _ n ( x ) = w _ ni ( x, w _ n1, … ? xnn ) y _ ni estimate the unknown function g ( x ). to the linear model y _ i - x _ i1 1 + … ? + x _ iq ? _ q, we use lse _ nj to estimate the unknown parametric _ j

    本篇論文主要是由兩大部分內容構成：一是關于誤差是l ~ p ?混合序列的線性回歸模型參數的最小二乘估計與非參數回歸模型未知函數的權函數估計的p ~ -階平均相合性和完全收斂性問題；另一部分是關于誤差是弱平穩線性過程的線性模型參數的最小二乘估計與非參數回歸模型未知函數的權函數估計的r ?階平均相合性和完全收斂性以及權函數估計的一致平均相合性問題。
  15. Firstly, the inversion of the ground motion with the unknown parameters and limited measurements was studied by the sub - structural identification, and the least - square algorithm of unknown input was built. secondly, based on the estimated input, structural parameter down to the element level was identified in time domain by extended kalman filter algorithm. several cases of a 6 - story frame s

    首先，使用子結構識別技術，研究了未知參數、觀測不完整條件下的地震動輸入反演問題，建立了未知輸入的最小二乘估計演算法；其次，在估計地震動輸入的基礎上，使用廣義kalman濾波器方法，識別全部單元結構參數。
  16. In the third section three different forms of heteroscedasticity are used in the random simulation and then park test, glejser test and goldfeld - quandt test are compared although the existence of heteroscedasticity does not destroy the unbiasedness of the ols estimators, the variances become larger

    異方差的存在雖然並不破壞普通最小二乘估計量的無偏性，但是估計量的方差變大了。由於估計量方差的變大，就使通常假設檢驗的值不可靠。
  17. 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
  18. Stochastic subspace identification method is the major in this article, and this method is based on the theory of projection of row space, and also uses qr decomposition, svd decomposition as well as least squares estimate to state space matrices of the discrete system so as to achieve the parameters of the dynamic behavior and it can achieve an accurate result

    隨機子空間法是本文的論述重點，它運用了行空間投影的理論，通過qr分解和svd分解以及最小二乘估計來識別離散后的系統狀態空間矩陣，從而得到系統的動力學特性參數，識別精度較高。本文詳細的推導了隨機子空間法的理論公式，並編寫出相應的matlab程序。
  19. Comparison of the estimator from the least - squares method with the robust method shows that the estimator from the robust estimator is more reliable

    通過比較，對于各測線上所有采樣點的系統誤差補償來說，系統誤差模型的抗差估計比最小二乘估計的可靠性更高。
  20. The least square estimate of covariance matrices in the growth curve model with random effects

    含有隨機效應的增長曲線模型協差陣的最小二乘估計
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