Differences

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

--- readme.aireml [2014/11/25 11:29] – shogo
+++ readme.aireml [2015/09/08 05:43] – [Options] dani
@@ Line 3: / Line 3: @@
 ===== Summary =====
 A modification of REMLF90 for estimating variances with the Average-Information algorithm. Initially written by Shogo Tsuruta in 03/99-07/99. AIREMLF90 uses a second derivative REML algorithm with extra heuristics, as is described in Jensen et al. (1996-7). For most models, it converges in far fewer rounds than EM-REML as implemented in REMLF90. While typically REMLF90 takes 50-300 rounds to converge, AIREMLF90 converges in 5-15 rounds and to a higher accuracy. The final results will be saved in "airemlf90.log".
+\\
 \\
 See PREGSF90 with genotypes (SNP) for options.
@@ Line 95: / Line 96: @@
 A formula to calculate a function of (co)variances to estimate SD. All terms of the function should be written with no spaces.\\
 \\
-Each term of the function corresponds to (co)variance elements and could include any random effects (G, PE, ...) and residual (R) (co)variances.\\
+Each term of the function corresponds to (co)variance elements and could include any random effects (G) and residual (R) (co)variances.\\
 \\
 Notation is with reference to the effect number and the trait number (''G_eff1_eff2_trt1_trt2'') that indicate the element of the (co)variance matrix for random effect ''eff1'' and ''eff2'' and ''trt1'' and ''trt2'',\\
@@ Line 141: / Line 142: @@
 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.
+where xx is the number of iterations for EM-REML you expect to get a good starting value for AI-REML. After running xx rounds with EM-REML, the AIREMLF90 program will automatically switch from EM-REML to AI-REML using the last estimate from EM-REML as a starting value for AI-REML.