Table 4 Correlations between EBV in the complete data: analyses with optimal and too low a fit within approaches, and analyses with optimal fits between approaches
From: Principal component and factor analytic models in international sire evaluation
Country | PC15 PC19 | FA7 FA9 | FA9 PC19 |
|---|---|---|---|
Canada | 0.999 | 1.000 | 1.000 |
Germany | 1.000 | 1.000 | 1.000 |
Denmark-Finland-Sweden | 1.000 | 1.000 | 1.000 |
France | 1.000 | 1.000 | 1.000 |
Italy | 1.000 | 1.000 | 1.000 |
The Netherlands | 1.000 | 1.000 | 1.000 |
USA | 1.000 | 1.000 | 1.000 |
Switzerland | 0.999 | 1.000 | 1.000 |
Great Britain | 1.000 | 1.000 | 1.000 |
New-Zealand | 0.995 | 0.997 | 0.999 |
Australia | 1.000 | 1.000 | 1.000 |
Belgium | 0.997 | 1.000 | 1.000 |
Ireland | 0.997 | 0.999 | 0.999 |
Spain | 1.000 | 1.000 | 1.000 |
Czech Republic | 0.993 | 0.997 | 0.999 |
Slovenia | 0.994 | 0.993 | 0.979 |
Estonia | 0.995 | 1.000 | 0.996 |
Israel | 0.985 | 0.985 | 0.993 |
Swiss Red Holstein | 0.999 | 1.000 | 0.999 |
French Red Holstein | 0.999 | 0.988 | 0.988 |
Hungary | 0.999 | 1.000 | 1.000 |
Poland | 0.999 | 1.000 | 0.999 |
South Africa | 0.992 | 0.995 | 0.998 |
Japan | 0.999 | 0.999 | 1.000 |
Latvia | 0.982 | 0.993 | 0.977 |