in_广义线性模型中极大拟似然估计的极限理论研究 热度: in_基于双线性与平方和最优化理论的吸引域估计 热度: ESTIMATl0NOFLINEAR ERRORS—IN—VARIABLES MODELS ZHf心『GHai (Department of Mathemtics, NorthWestUniversit y,Xi’an,710069) Abstract Inthis ...
实证检验中两个问题变量中的误差(Errors-in-Variables),Lintner先对每个样 本股票估计各自 βi 值(时间序列估计),然后利用估 … wenku.baidu.com|基于3个网页 3. 变量误差 这一替代会产生古典的变量误差(errors-in-variables)问ii1i题,因为在横截面回归模型(2.4)中b的回归元存在测量误差。用时间 … ...
While parameter bounding methods and algorithms have been extensively developed in the case of exactly known regressor variables, little attention has been paid to the bounded errors-in-variables problem. This chapter gives a formal proof of a previous result on the description of the feasible ...
1.我看了之后,觉得因为题目中回填等操作使得获取的report return变量其实本身就有偏差(会被高估)了,为什么不属于errors-in-variables bias? 2.所以这个bias主要指在操作上出现的问题,例如漏了变量、模型运算等操作风险事件上吗,。而不是说变量input选的数据集不好?添加评论 0 0 1 个答案 已采纳答案 袁园_品...
When the errors are normally distributed with zero mean and constant variance, and the model is exact, then the standard least-squares fit gives the maximum-likelihood solution. In some cases, however, the errors in both dependent and independent variables may be comparable. This situation has a...
errors- in-variablespersistenceThis paper proposes a wavelet (spectral) approach to estimate the parameters of a linear regression model where the regressand and the regressors are persistent processes and contain a measurement error. We propose a wavelet filtering approach which does not require ...
Common Slope Tests for Bivariate Errors-in-Variables Models 热度: Instrumental variables estimation in errors-in-variables models when instruments are correlated with errors 热度: Exhibition-of-Master-Wan-Ko-Yee's-Amazing-Achievement-in-the-Form-of-World-Class-Treasures ...
主题词： 预测 回归分析 Errors-in-Variables（EIV） 结构关系模型 摘要：预测是统计学实际应用的一个主要方面,多元线性回归预测是一种很好的方法,广泛地应用在各种实际领域,但其局限性及不足也是明显的.本文以一种新的观点认识数据,即认为变量的观测里均含有误差,同时认为不应删除经慎重选择进来的解释变量.为此,...
Errors-in-variables Estimation for Gaussian Lattice Schemes," Journal of the Royal Statistical Society, Series B: Methodological, 39, 73-78.Besag, J.E. 1977. Errors-in-variables estimation for Gaussian lattice schemes. J. R. Statust. Soc. Ser. B 39:73-78....
This paper considers the problem of filtering data sequences generated by errors-in-variables processes where all measured signals, differently from the classical Kalman filtering context, are affected by additive noise. The design of optimal (minimal variance) filters leading to estimates of the proce...