User Tools

Site Tools


readme.reml

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision
Previous revision
Next revisionBoth sides next revision
readme.reml [2013/07/17 16:19] shogoreadme.reml [2014/01/22 19:53] shogo
Line 1: Line 1:
 ====== REMLF90 ====== ====== REMLF90 ======
-Variance component estimation program with EM-REML algorithm. 
-See PREGSF90 with genotypes (SNP) for options. 
  
 ===== Summary ===== ===== Summary =====
-The final results will be saved in "REMLF90.log".+Variance component estimation program with EM-REML algorithm. The final results will be saved in "REMLF90.log"
 +\\ 
 +See PREGSF90 with genotypes (SNP) for options.
  
 ===== Options ===== ===== Options =====
Line 15: Line 15:
 </file> </file>
 Maximum rounds (default 5000). Maximum rounds (default 5000).
 +<file>
 +OPTION use_yams
 +</file>
 +Run the program with YAMS (modified FSPAK). The computing time can be dramatically improved.
 <file> <file>
 OPTION constant_var 5 1 2 OPTION constant_var 5 1 2
Line 29: Line 33:
 ===== Does remlf90 always converge? ===== ===== Does remlf90 always converge? =====
 Even when there is no variance, remlf90 will estimate a positive variance (within the parameter space), which will be determined by the starting value. If you are not sure if there is any variance, use a small starting value such as 0.1 or 0.01. If the estimate does not change, probably there is no variance, so check your parameter file, model, and/or data again. If airemlf90 does not converge but remlf90 converges with the same data set and the same model, rerun remlf90 with a small starting value because the estimate could be artifact. Even when there is no variance, remlf90 will estimate a positive variance (within the parameter space), which will be determined by the starting value. If you are not sure if there is any variance, use a small starting value such as 0.1 or 0.01. If the estimate does not change, probably there is no variance, so check your parameter file, model, and/or data again. If airemlf90 does not converge but remlf90 converges with the same data set and the same model, rerun remlf90 with a small starting value because the estimate could be artifact.
- 
  
readme.reml.txt · Last modified: 2024/03/25 18:22 by 127.0.0.1

Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki