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--- readme.aireml [2014/07/09 12:16] – andres
+++ readme.aireml [2014/09/05 16:16] – shogo
@@ Line 16: / Line 16: @@
 OPTION maxrounds 1000
 </file>
-Maximum rounds (default 5000). When the number < 2, the program calculates BLUP without iterating REML.
+Maximum rounds (default 5000). When the number = 0, the program calculates BLUP without iterating REML and some statistics (-2logL, AIC, SE for (co)variances, ...).
 <file>
 OPTION EM-REML 10
@@ Line 33: / Line 33: @@
 OPTION sol se
 </file>
-Store solutions and those s.e.
+Store solutions and those standard errors.
+<file>
+OPTION store_pev_pec 6
+</file>
+Store triangular matrices of standard errors and its covariances for correlated random effects such as direct-maternal effects and random-regression effects in "pev_pec_bf90".
 <file>
 OPTION residual
@@ Line 42: / Line 46: @@
 </file>
 Specify the missing value (default 0).
+<file>
+OPTION constant_var 5 1 2 ...
+</file>
+: effect number\\
+: first trait number\\
+: second trait number\\
+implying the covariance between traits 1 and 2 for effect 5.
 **Heterogeneous residual variances for a single trait**
@@ Line 78: / Line 89: @@
 <file>OPTION se_covar_function <label> <function></file>
-Calculate SD for function of (co)variances by repeated sampling of parameters estimates from their asymptotic multivariate normal distribution, following idea presented by Meyer and Houle 2013.
+As an alternative of SE, calculate SD for function of (co)variances by repeated sampling of parameters estimates from their asymptotic multivariate normal distribution, following idea presented by Meyer and Houle 2013.\\
+\\
-''<label>'' given name for a particular function\\
+''<label>''\\
-''<function>'' function of (co)variances to estimate SD, all elements of the function should be written with no spaces.\\
+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>''\\
+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.\\
+\\
+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.\\
 \\
-Each element of the function corresponds to (co)variances elements and could include any the random effects (G) and residual (R) (co)variances.\\
-Notation is with reference to the effect and trait number:\\
-''G_eff1_eff2_trt1_trt2'': indicate the element of the (co)variance matrix for random effect ''eff1'' and ''eff2'' and ''trt1'' and ''trt2'', where ''eff1'', ''eff2'' are the effect number, and ''trt1'' and ''trt2'' the trait number\\
-''R_trt1_trt1'': indicate the element of the residual (co)variance matrix for traits ''trt1'' and ''trt2''
-Several functions could be added, with one OPTION line per function.
 Examples:\\
 \\
-''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''\\
+\\
 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.
-The second function calculates the heritability for the direct component and the third function the total heritability.
+The second function calculates the heritability for the direct component.
-The fourth function calculates the SD of the genetic correlation between traits 1 and 2, for the direct genetic effect (effect number 2)
+The third function the total heritability.
+The fourth function calculates the SD of the genetic correlation between traits 1 and 2 for the direct genetic effect (effect number 2)
 <file>OPTION samples_se_covar_function <n></file>
@@ Line 111: / Line 128: @@
 <file>OPTION out_se_covar_function</file>
 Indicate to store in file samples of (co)variances function for postprocessing (histogram, etc.)