optimizeByLOESS.RdFunction to optimize a two-part strategy breeding scheme: 1. Simulate a batch using given percentage ranges 2. Perform LOESS fit to the gains 3. Find budget with best estimated gain 4. Calculate new percentage ranges: any simulation within 2*StdErr of best 5. Decide on some simulations to repeat: 1. Parameter space with high gain and high std err: need more info there 2. Parameter space with high gain: high probability that it's best Go back to 1.
optimizeByLOESS(bsd)
| bsd | List of breeding scheme data. Has parameters for optimization too. |
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Numeric matrix with all simulation budget allocations, gen mean change, gen std dev change, total cost.
A wrapper to repeatedly simulate a scheme with different budget allocations to find optimal allocations