GLS DISCREPANCY BASED INFORMATION CRITERIA FOR SELECTING COVARIANCE STRUCTURE MODELS
スポンサーリンク
概要
- 論文の詳細を見る
- 2010-07-01
著者
-
Yanagihara Hirokazu
Department Of Electrical Engineering Faculty Of Engineering Kanazawa Institute Of Technology
-
HIMENO Tetsuto
Graduate School of Mathematics, Kyushu University
-
YUAN Ke-Hai
Department of Psychology, University of Notre Dame
-
Yuan Ke-hai
Department Of Psychology University Of California
-
Himeno Tetsuto
Graduate School Of Mathematics Kyushu University
関連論文
- Variable Selection in Multivariate Linear Regression Models with Fewer Observations than the Dimension
- CONDITIONS FOR ROBUSTNESS TO NONNORMALITY ON TEST STATISTICS IN A GMANOVA MODEL
- Adjustment on an asymptotic expansion of the distribution function with $χ^2$-approximation
- GLS DISCREPANCY BASED INFORMATION CRITERIA FOR SELECTING COVARIANCE STRUCTURE MODELS
- Asymptotic expansions of the null distributions of three test statistics in a nonnormal GMANOVA model
- Dielectric Dispersion and Soft Mode in Rochelle Salt
- Study of Ferroelectric Soft Mode in Li_2Ge_7O_ by Microwave Dielectric Spectroscopy
- ASYMPTOTIC RESULTS OF A HIGH DIMENSIONAL MANOVA TEST AND POWER COMPARISON WHEN THE DIMENSION IS LARGE COMPARED TO THE SAMPLE SIZE
- FINITE SAMPLE DISTRIBUTION-FREE TEST STATISTICS FOR NESTED STRUCTURAL MODELS
- Asymptotic expansions of the null distribution for the Dempster trace criterion