Estimation on principal component of multi-collinearity Gauss-Markov model based on minimum description length
来源期刊:中国有色金属学报(英文版)2005年第z1期
论文作者:SHI Yu-feng
文章页码:145 - 147
Key words:minimum description length; Gauss-Markov model; multi-collinearity; principal component estimation
Abstract: Gauss-Markov model is frequently used in data analysis; the analysis and estimation of its parameters is always a hot issue. Based on the information theory and from the viewpoint of optimal information on description—minimum description length, this paper discusses a case: where there is multi-collinearity in the coefficient matrix, principal component estimation is used to estimate and select the original parameters, so as to reduce its multi-collinearity and improve its credibility. From the viewpoint of minimum description length, this paper discusses the approach of selecting principal components and uses this approach to solve a practical problem.