Estimating sampling error of evolutionary statistics based on genetic covariance matrices using maximum likelihood

2015 ◽  
Vol 28 (8) ◽  
pp. 1542-1549 ◽  
Author(s):  
D. Houle ◽  
K. Meyer
2005 ◽  
Vol 57 (1-2) ◽  
pp. 49-66 ◽  
Author(s):  
Anuradba Roy ◽  
Ravindra Khattree

In repeated measures studies how observations change over time is often of prime interest. Modelling this time effect in the context of discrimination, is the objective of this article. We study the problem of classification with multiple q-variate observations with time effect on each individual. The covariance matrices as well as mean vectors are mordelled respectively to accommodate the correlation between the successive repeated measures and to describe the time effects. Computation schemes for maximum likelihood estimation of required population parameters are provided.


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