The INBREED Procedure
The OUTCOV= data set has the following variables:
-
a list of BY variables, if there is a BY statement
-
the generation variable, if there is a CLASS statement
-
the gender variable, if there is a GENDER statement
-
_Type_, a variable indicating the type of observation. The valid values of the_Type_variable are ‘COV’ for covariance estimates and ‘INBREED’ for inbreeding coefficients. -
_Panel_, a variable indicating the panel number used when populations delimited by BY groups contain different numbers of individuals. If there are n individuals in the first BY group and if any subsequent BY group contains a larger population, then its covariance/inbreeding matrix is divided into panels, with each panel containing n columns of data. If you put these panels side by side in increasing_Panel_number order, then you can reconstruct the covariance or inbreeding matrix. -
_Col_, a variable used to name columns of the inbreeding or covariance matrix. The values of this variable start with ‘COL’, followed by a number indicating the column number. The names of the individuals corresponding to any given column i can be found by reading the individual’s name across the row that has a_Col_value of ‘COLi’. When the inbreeding or covariance matrix is divided into panels, all the rows repeat for the first n columns, all the rows repeat for the next n columns, and so on. -
the variable containing the names of the individuals, that is, the first variable listed in the VAR statement
-
the variable containing the names of the first parents, that is, the second variable listed in the VAR statement
-
the variable containing the names of the second parents, that is, the third variable listed in the VAR statement
-
a list of covariance variables
Col1–Coln, where n is the maximum number of individuals in the first population
The functions of the variables _Panel_ and _Col_ can best be demonstrated by an example. Assume that there are three individuals in the first BY group and that, in the current
BY group (Byvar=2), there are five individuals with the following covariance matrix.
|
COV |
1 |
2 |
3 |
4 |
5 |
|---|---|---|---|---|---|
|
1 |
Cov(1,1) |
Cov(1,2) |
Cov(1,3) |
Cov(1,4) |
Cov(1,5) |
|
2 |
Cov(2,1) |
Cov(2,2) |
Cov(2,3) |
Cov(2,4) |
Cov(2,5) |
|
3 |
Cov(3,1) |
Cov(3,2) |
Cov(3,3) |
Cov(3,4) |
Cov(3,5) |
|
4 |
Cov(4,1) |
Cov(4,2) |
Cov(4,3) |
Cov(4,4) |
Cov(4,5) |
|
5 |
Cov(5,1) |
Cov(5,2) |
Cov(5,3) |
Cov(5,4) |
Cov(5,5) |
|
Panel 1 |
Panel 2 |
||||
Then the OUTCOV= data set appears as follows.
|
|
|
|
|
|
|
|
|
|
|---|---|---|---|---|---|---|---|---|
|
2 |
1 |
COL1 |
1 |
Cov(1,1) |
Cov(1,2) |
Cov(1,3) |
||
|
2 |
1 |
COL2 |
2 |
Cov(2,1) |
Cov(2,2) |
Cov(2,3) |
||
|
2 |
1 |
COL3 |
3 |
Cov(3,1) |
Cov(3,2) |
Cov(3,3) |
||
|
2 |
1 |
4 |
Cov(4,1) |
Cov(4,2) |
Cov(4,3) |
|||
|
2 |
1 |
5 |
Cov(5,1) |
Cov(5,2) |
Cov(5,3) |
|||
|
2 |
2 |
1 |
Cov(1,4) |
Cov(1,5) |
. |
|||
|
2 |
2 |
2 |
Cov(2,4) |
Cov(2,5) |
. |
|||
|
2 |
2 |
3 |
Cov(3,4) |
Cov(3,5) |
. |
|||
|
2 |
2 |
COL1 |
4 |
Cov(4,4) |
Cov(4,5) |
. |
||
|
2 |
2 |
COL2 |
5 |
Cov(5,4) |
Cov(5,5) |
. |
Notice that the first three columns go to the first panel (_Panel_=1), and the remaining two go to the second panel (_Panel_=2). Therefore, in the first panel, ‘COL1’, ‘COL2’, and ‘COL3’ correspond to individuals 1, 2, and 3, respectively, while
in the second panel, ‘COL1’ and ‘COL2’ correspond to individuals 4 and 5, respectively.