Breeding values are typically estimated from multiple sources of information (own performance, sibs, etc.). Combining these sources ensures that we optimize the accuracy of the estimated breeding values (EBV). To get the most accurate EBV, we need to find the optimal weights that should be used for each information source. These weights can be computed using selection index theory, which is implemented in the tool below. This tool allows to compute the optimal index weights for two traits that are correlated.
Simply adjust the parameters, enter the number of records you have for each information source, and click “Compute Index”. The output will show the accuracy of the index, the optimal weights for each of the information sources, and the response to selection for each of the traits.
I acknowledge Prof. Julius van der Werf (https://jvanderw.une.edu.au/), whose Excel sheet provided the basis and inspiration for this tool. Note that this tool assumes that common and permanent environmental effects across traits are uncorrelated.