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--- readme.aireml [2014/07/10 13:24] – shogo
+++ readme.aireml [2014/07/10 13:29] – shogo
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 ''<label>''\\
-A name for a particular function (e.g., P1 for phenotypic variance of trait 1, H2_1 for heritability for trait 1, rg12 for genetic correlation between traits 1 and 2, …).\\
+A name for a particular function (e.g., ''P1'' for phenotypic variance of trait 1, ''H2_1'' for heritability for trait 1, ''rg12'' for genetic correlation between traits 1 and 2, …).\\
 \\
 ''<function>''\\
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 Each term of the function corresponds to (co)variance elements and could include any random effects (G, PE, ...) and residual (R) (co)variances.\\
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-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'', where ''eff1'' and ''eff2'' are effect numbers 1 and 2, and ''trt1'' and ''trt2'' are trait numbers 1 and 2.\\
+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'',\\
+where ''eff1'' and ''eff2'' are effect numbers 1 and 2, and ''trt1'' and ''trt2'' are trait numbers 1 and 2.\\
 ''R_trt1_trt1'' indicates the element of the residual (co)variance matrix for traits 1 and 2.\\
+\\
 Several functions could be added, with one OPTION line per function.\\
 \\
 Examples:\\
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-''OPTION se_covar_function P   G_2_2_1_1+G_2_3_1_1+G_3_3_1_1+G_4_4_1_1+R_1_1''\\
+''OPTION se_covar_function  P  G_2_2_1_1+G_2_3_1_1+G_3_3_1_1+G_4_4_1_1+R_1_1''\\
-''OPTION se_covar_function H2d   G_2_2_1_1/(G_2_2_1_1+G_2_3_1_1+G_3_3_1_1+G_4_4_1_1+R_1_1)''\\
+''OPTION se_covar_function  H2d  G_2_2_1_1/(G_2_2_1_1+G_2_3_1_1+G_3_3_1_1+G_4_4_1_1+R_1_1)''\\
-''OPTION se_covar_function H2t (G_2_2_1_1+1.5*G_2_3_1_1+0.5*G_3_3_1_1)/(G_2_2_1_1+G_2_3_1_1+G_3_3_1_1+G_4_4_1_1+R_1_1)''\\
+''OPTION se_covar_function  H2t  (G_2_2_1_1+1.5*G_2_3_1_1+0.5*G_3_3_1_1)/(G_2_2_1_1+G_2_3_1_1+G_3_3_1_1+G_4_4_1_1+R_1_1)''\\
-''OPTION se_covar_function rg12 G_2_2_1_2/((G_2_2_1_1*G_2_2_2_2)**0.5)''\\
+''OPTION se_covar_function  rg12  G_2_2_1_2/(G_2_2_1_1*G_2_2_2_2)**0.5''\\
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 The first function calculates the SD for the total variance for a maternal model with permanent maternal effect, where 2 and 3 are the effect number for the direct and maternal additive genetic effects respectively, and 4 is the effect number for the maternal permanent random effect.