HW Solutions Stat 36

HW Solutions Stat 36 - Chapter 13 INTRODUCTION TO NONLINEAR...

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Chapter 13 INTRODUCTION TO NONLINEAR REGRESSION AND NEURAL NETWORKS 13.1. a. Intrinsically linear log e f ( X , γ )= γ 0 + γ 1 X b. Nonlinear c. Nonlinear 13.3. b. 300, 3.7323 13.5. a. b 0 = . 5072512, b 1 = 0 . 0006934571, g (0) 0 =0 , g (0) 1 = . 0006934571, g (0) 2 = . 6021485 b. g 0 = . 04823, g 1 = . 00112, g 2 = . 71341 13.6. a. ˆ Y = . 04823 + . 71341exp( . 00112 X ) City A i :1 2 3 4 5 ˆ Y i : . 61877 . 50451 . 34006 . 23488 . 16760 e i : . 03123 . 04451 . 00006 . 02512 . 00240 Exp. value: . 04125 . 04125 . 00180 . 02304 . 00180 i :6 7 8 ˆ Y i : . 12458
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