Full data set:
12.0 1.0 1.0
32.0 10.0 1.0
103.0 100.0 1.0
20.0 1.0 10.0
61.0...
13.17. Process yield. The yield (Y) of a chemical process depends on the temperature (X1) and pressure (X2). The following nonlinear regression model is expected to be applicable: Prior to beginning full-scale production, 18 tests were undertaken to study the process yield for various temperature and pressure combinations. The results follow. 18 100 100 398 16 17 2 100 100 43 100 128 32 103 a. To obtain starting values for yo, Vi, and V2, note that when we ignore the random error term, a logarithmic transformation yields Y- Po + AiX + B Xi2, where Y-log10 Yi, Po logo为, β,-M , Xİı = logo Xil, A = ½, and Xa = logo Xi2. Fit a first-order multiple regression model to the transformed data, and use as starting values go - antilogio bo, 8b, and 82 -b2 b. Using the starting values obtained in part (a), find the least squares estimates of the param eters ro, n, and ½