readme.aireml
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revisionNext revisionBoth sides next revision | ||
readme.aireml [2014/07/10 13:19] – shogo | readme.aireml [2014/09/05 16:10] – shogo | ||
---|---|---|---|
Line 33: | Line 33: | ||
OPTION sol se | OPTION sol se | ||
</ | </ | ||
- | Store solutions and those s.e. | + | Store solutions and those standard errors. |
+ | < | ||
+ | OPTION store_pev_pec 6 | ||
+ | </ | ||
+ | Store triangular matrices of standard errors and its covariances for correlated random effects such as direct-maternal effects and random-regression effects in " | ||
< | < | ||
OPTION residual | OPTION residual | ||
Line 42: | Line 46: | ||
</ | </ | ||
Specify the missing value (default 0). | Specify the missing value (default 0). | ||
+ | < | ||
+ | OPTION constant_var 5 1 2 ... | ||
+ | </ | ||
+ | 5: effect number\\ | ||
+ | 1: first trait number\\ | ||
+ | 2: second trait number\\ | ||
+ | implying the covariance between traits 1 and 2 for effect 5. | ||
**Heterogeneous residual variances for a single trait** | **Heterogeneous residual variances for a single trait** | ||
Line 78: | Line 89: | ||
< | < | ||
- | As an alternative of SE, calculate SD for function of (co)variances by repeated sampling of parameters estimates from their asymptotic multivariate normal distribution, | + | As an alternative of SE, calculate SD for function of (co)variances by repeated sampling of parameters estimates from their asymptotic multivariate normal distribution, |
- | + | \\ | |
- | ''< | + | ''< |
- | ''< | + | A name for a particular function (e.g., |
+ | \\ | ||
+ | ''< | ||
+ | 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, 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 '' | + | \\ |
- | '' | + | Notation is with reference to the effect number and the trait number ('' |
- | + | where '' | |
- | Several functions could be added, with one OPTION line per function. | + | '' |
+ | \\ | ||
+ | Several functions could be added, with one OPTION line per function.\\ | ||
+ | \\ | ||
Examples:\\ | Examples:\\ | ||
\\ | \\ | ||
- | '' | + | '' |
- | '' | + | '' |
- | '' | + | '' |
- | + | ||
- | '' | + | |
+ | '' | ||
+ | \\ | ||
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, | 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, | ||
readme.aireml.txt · Last modified: 2024/03/25 18:22 by 127.0.0.1