Multivariate joint normal likelihood distance

다국어 초록 (Multilingual Abstract)

The likelihood distance for the joint distribution of two multivariate normal distributions
with common covariance matrix is explicitly derived. It is useful for
identifying outliers which do not follow the joint multivariate normal distribution with common covariance matrix.
The likelihood distance derived here is a good ground for the use of a generalized Wilks statistic in influence analysis of two multivariate normal data.

다국어 초록 (Multilingual Abstract)

The likelihood distance for the joint distribution of two multivariate normal distributions
with common covariance matrix is explicitly derived. It is useful for
identifying outliers which do not follow the joint multivariate normal distribution with common covariance matrix.
The likelihood distance derived here is a good ground for the use of a generalized Wilks statistic in influence analysis of two multivariate normal data.

참고문헌 (Reference)

1 M. G. Kim, "The influence in comparing covariance matrices" 24 : 1431-1441, 1995

2 K.-M. Jung, "Second order local influence in linear discriminant analysis" 10 : 1-11, 1997

3 S. S. Wilks, "Multivariate statistical outliers" 25 : 407-426, 1963

4 K. V. Mardia, "Multivariate Analysis" Academic Press 1979

5 김명근, "Influence on Hotelling's Test Statistic" 한국자료분석학회 9 (9): 545-551, 2007

6 K.-M. Jung, "Influence analysis in selecting discriminant variables" 30 : 499-509, 2001

7 M. G. Kim, "Case influence on multiple correlation coefficient" 19 : 521-525, 2005