!VPGROUP f1 [f2] [f3]facilitates putting (equality) constraints across residual variance parameters. The residual model
sat(Exp).ar1(Row).ar1v(Col)defines the spatial residual model where each experiment (Exp) is laid out as a Row/Col grid with autoregressive (ar) correlations across rows and columns (as a direct product) and a common variance (v) within each section. Sometimes, the grids may be small and grouped in some way and the user wants the parameters to be constrained to be equal across sections/grids within groups. For example
residual sat(Exp !VPGROUP Group1 Group2 Group3).ar1(Row).ar1v(Col)where Groupi (i=1,2,3) are variables that group the data records associated with Exp. This example has 3 spatial parameters for each experiment in the order row correlation, column correlation and variance. ASReml will constain the i-th parameter according to Groupi (i=1,2,3). If only one grouping factor is listed, it will be used for all three parameters.
residual sat(Exp !VPGROUP mu Field Exp).ar1(Row).ar1v(Col)allows a common row autocorrelation across all sections, a field specific column autocorrelation and a distinct variance for each section. % If the same grouping is applied to all parameters the specification can be reduced to sat(Exp !VPGROUP Group1).ar1(Row).ar1v(Col)
| VCC statement | action | ||
| VCC idv(units) !LINK 1 2 !SCALE 1 -1 VCC idv(units) !LINK 1 -2 VCC idv(units) -uni(Check) |
These three statements are equivalent and cause the parameter following units ( uni(Check)) in the following code sample, if placed after the residual line, to have the same magnitude but opposite sign as the parameter for units. y ~ mu Cov Ch mv !r, idv(units !INIT 1) uni(Check !INIT -1) residual ar1v(Col):id(Row) VCC us(Env).idv(blocks) !LINK 2 4 5 7 8 9 |
For a (4 × 4) US matrix us(Env), the covariances are made equal.
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