readme.aireml
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readme.aireml [2014/09/05 16:10] – shogo | readme.aireml [2014/11/25 11:29] – shogo | ||
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===== Summary ===== | ===== Summary ===== | ||
- | A modification of REMLF90 for estimating variances with the Average-Information algorithm. Initially written by Shogo Tsuruta in 03/ | + | A modification of REMLF90 for estimating variances with the Average-Information algorithm. Initially written by Shogo Tsuruta in 03/ |
- | \\ | + | |
- | AIREMLF90 uses a second derivative REML algrithm | + | |
\\ | \\ | ||
See PREGSF90 with genotypes (SNP) for options. | See PREGSF90 with genotypes (SNP) for options. | ||
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OPTION maxrounds 1000 | OPTION maxrounds 1000 | ||
</ | </ | ||
- | Maximum rounds (default 5000). When the number | + | Maximum rounds (default 5000). When the number |
< | < | ||
OPTION EM-REML 10 | OPTION EM-REML 10 | ||
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< | < | ||
Indicate to store in file samples of (co)variances function for postprocessing (histogram, etc.) | Indicate to store in file samples of (co)variances function for postprocessing (histogram, etc.) | ||
+ | |||
+ | ===== Tricks ===== | ||
+ | When the covariance matrix is close to non-positive definite, the AIREMLF90 may not converge. | ||
+ | There are two options you might want to try: | ||
+ | |||
+ | 1. change the tolerance value (xx) in the option: | ||
+ | |||
+ | OPTION tol xx | ||
+ | |||
+ | to a very strict value (e.g., 1d-20) or a lenient value (1d-06). | ||
+ | |||
+ | 2. use an option to use EM-REML inside AI-REML: | ||
+ | |||
+ | OPTION EM-REML xx | ||
+ | |||
+ | where xx is the number of iterations for EM-REML you expect to get a good starting value for AI-REML. | ||
+ |
readme.aireml.txt · Last modified: 2024/03/25 18:22 by 127.0.0.1