Lasso Maximum Likelihood Estimation of Parametric Models with Singular Information Matrices

doi:10.3390/econometrics6010008

CORC > 上海财经大学 > 上海财经大学

	Lasso Maximum Likelihood Estimation of Parametric Models with Singular Information Matrices
	Jin, Fei 1,2; Lee, Lung-fei 3
刊名	ECONOMETRICS
	2018-03
卷号	6 期号:1
关键词	penalized maximum likelihood singular information matrix lasso oracle properties
ISSN号	2225-1146
DOI	10.3390/econometrics6010008
英文摘要	An information matrix of a parametric model being singular at a certain true value of a parameter vector is irregular. The maximum likelihood estimator in the irregular case usually has a rate of convergence slower than the root n-rate in a regular case. We propose to estimate such models by the adaptive lasso maximum likelihood and propose an information criterion to select the involved tuning parameter. We show that the penalized maximum likelihood estimator has the oracle properties. The method can implement model selection and estimation simultaneously and the estimator always has the usual root n-rate of convergence.
WOS研究方向	Business & Economics
语种	英语
出版者	MDPI
WOS记录号	WOS:000428554400004
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/672]
专题	上海财经大学
通讯作者	Lee, Lung-fei
作者单位	1.Shanghai Univ Finance & Econ, Sch Econ, Shanghai 200433, Peoples R China; 2.Minist Educ, Key Lab Math Econ SUFE, Shanghai 200433, Peoples R China; 3.Ohio State Univ, Dept Econ, Columbus, OH 43210 USA
推荐引用方式 GB/T 7714	Jin, Fei,Lee, Lung-fei. Lasso Maximum Likelihood Estimation of Parametric Models with Singular Information Matrices[J]. ECONOMETRICS,2018,6(1).
APA	Jin, Fei,&Lee, Lung-fei.(2018).Lasso Maximum Likelihood Estimation of Parametric Models with Singular Information Matrices.ECONOMETRICS,6(1).
MLA	Jin, Fei,et al."Lasso Maximum Likelihood Estimation of Parametric Models with Singular Information Matrices".ECONOMETRICS 6.1(2018).