Determining the number of factoArs is essential to factor analysis. In this paper, we propose an efficient cross validation (CV) method to determine the number of factors in the approximate factor model. The method applies CV twice, first along the direction of the observations and then the direction of the variables, and hence is referred to hereafter as double cross-validation (DCV). Unlike most CV methods, which are prone to overfitting, DCV is statistically consistent in determining the number of factors when both dimensions of variables and sample size are sufficiently large. Simulation studies show that DCV has outstanding performance in comparison to existing methods in selecting the number of factors, especially when the idiosyncratic error has heteroscedasticity, or heavy tail, or relatively large variance.

6月15日
2pm - 3pm
地點
Room 2463 (Lifts 25/26)
講者/表演者
Prof. Yingcun XIA
Department of Statistics and Applied Probability, National University of Singapore
主辦單位
Department of Mathematics
聯絡方法
付款詳情
對象
Alumni, Faculty and staff, PG students, UG students
語言
英語
其他活動
6月21日
研討會, 演講, 講座
IAS / School of Science Joint Lecture - Alzheimer’s Disease is Likely a Lipid-disorder Complication: an Example of Functional Lipidomics for Biomedical and Biological Research
Abstract Functional lipidomics is a frontier in lipidomics research, which identifies changes of cellular lipidomes in disease by lipidomics, uncovers the molecular mechanism(s) leading to the chan...
5月24日
研討會, 演講, 講座
IAS / School of Science Joint Lecture - Confinement Controlled Electrochemistry: Nanopore beyond Sequencing
Abstract Nanopore electrochemistry refers to the promising measurement science based on elaborate pore structures, which offers a well-defined geometric confined space to adopt and characterize sin...