When I run the following code, I get a warning message as follows: "WARNING: The number of response pairs for estimating correlation is less than or equal to the number of regression parameters. A simpler correlation model might be more appropriate. WARNING: The generalized Hessian matrix is not positive definite. Iteration will be terminated." NB: The program is executed normally till the end, convergence was attained, but when I tried different covariance options in the "type = AR(1)" or UN, or CS, etc., all estimates and standard errors are thesame for different covariance structures that i used. I wanted to look for the covariance structure that produces the smallest QIC value. Unfortunatell for me, all covariance structures used gave same empirical estimates and standard errors. Also when I specify the CORRW in the repeated statement, the working correlation matrix is same for all structures of covariance verified. i.e diagonals are ones and others zeros. Please I need your help, especially in the warning message above, and to have varying results for different covariance options used. Thanks.
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