例句與造句

1. 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(yōu)加權(quán)最小二乘估計也利用有關(guān)被估參數(shù)的先驗信息時，二者的估計性能。
2. Two indexes was calculated to estimate the best bands union for color combination , one is optimum index factor ( oif , the sum of standard deviation divided by the sum of correlation coefficient . ) , the other is the determinant of the co - variance matrix . it can be seen from the result that for color combination the original optimal bands were tm 4 , 3 , 7 and tm 4 , 3 , 5 , the best mixed images were mnf1 , br and ndvi
   以協(xié)方差矩陣行列式值和最佳指數(shù)值(組合波段標準差之和除以相關(guān)系數(shù)之和)為評價標準，得出對于tm原始波段而言，最佳的彩色合成組合是tm4 、 3 、 7和tm4 、 3 、 5 ；綜合幾種變換圖像的彩色合成的最佳組合是mnf1 、 br 、 ndvi 。
3. 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(guān)被估參數(shù)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(yōu)加權(quán)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(shè)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(yōu)加權(quán)最小二乘估計達到與線性最小方差估計一樣優(yōu)越的估計性能。
4. When the covariance matrix formed by securities yields is non - oppositive definite , we provide the model with transaction costs , which risk is variance matrix risk . when the covariance matrix formed by securities yields is not exist , the risk we use is absolute deviation risk and semi - absolute deviation , which is differ with traditional risk such as variance matrix risk or semi - variance matrix risk
   在證券收益率協(xié)方差陣不一定存在時，給出了不同于以往以證券收益率間的方差或是半方差為風險度量指標而是以絕對離差為風險指標和以半絕對離差為風險指標的含有交易費用的證券組合投資模型。
5. Chapter 2 : using a so - called variance matrix , we studied the propagation and the focusing characteristics of the paraxial light beams . the quantities characterizing the gross features for a paraxial optical beam , such as the beam width , the divergence , the curvature radius of the wavefront , the complex beam parameter q . and the beam quality factor , are related by using variance matrix
   第二章：闡述了常數(shù)折射率介質(zhì)中光束的傳輸和聚焦，建立了表征傍軸光束總的特征的量，如：束寬、衍射發(fā)散角、波前曲率半徑、復光束參數(shù)q與變換矩陣的關(guān)系，得到了光束質(zhì)量因子和變換矩陣行列式的定量關(guān)系。
6. It's difficult to find variance matrix in a sentence. 用variance matrix造句挺難的
7. Following , making development study from the three directions : the first one is how to reduce calculation when to use markowitz model . this text has improved the efficient frontier of markowitz model utilizing free risk assets , and reduced calculation about revenue rates " co - variance matrix utilizing single or multiple factors , and so on . the second one is to add thinking factors about , such as transaction fee , fund limitation , lowest transaction unit ' s limitation , risk measures and exchange rate risk of international portfolio securities , so as to make markowitz model closer to our country ' s practice
   接著，分三今方向?qū)arkowitz模型進行了拓展研究：第一個方向是運用markowitz模型時如何減少計算量，本文利用無風險資產(chǎn)來改進markowitz模型的有效邊界，利用單因子或多因子模型來減少收益率協(xié)方差的計算量等等；第二個方向是增加考慮因素，諸如交易費用、資金限制、最小交易單位限制，風險測度和國際組合證券的匯率風險，使markowitz模型更貼近我國的實際；第三個方向是對markowitz模型進行動態(tài)拓展研究，提出了將證券收益率看成是隨機序列時的投資決策模型，深入研究了m ? v有效邊界隨資產(chǎn)品種數(shù)增加而發(fā)生的漂移，并用解析方法和幾何圖形描述了漂移的軌跡和方向。