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--- readme.reml [2014/11/25 11:34] – shogo
+++ readme.reml [2015/06/16 20:11] – shogo
@@ Line 44: / Line 44: @@
 ===== Does REMLF90 always converge? =====
-When the expected variance is very small or the covariance matrix is close to non-positive definite, try with two different starting values (e.g., much smaller = 0.00001 and much bigger = 1000 when the expected variance is between 0 and 10).
+When the expected variance is very small or the covariance matrix is close to non-positive definite, try with two different starting values (e.g., much smaller = 0.00001 and much bigger = 1000 when the expected variance is between 0 and 1).
 The REMLF90 program will always estimate a positive variance (within the parameter space) even if there is no variance (using wrong data or format and/or a completely wrong model).
 If AIREMLF90 does not converge but REMLF90 converges with the same data set and the same model, rerun REMLF90 with a small starting value to check the estimate because it could be artifact.