The Hardest Interview 2 [ 8K • 2K ]

Given uniform prior (\lambda \sim U[0.05,0.15]), after seeing (m) other families’ early stops, they update via Bayes. The problem becomes a with incomplete information. 6. Key Result (Numerical Simulation Summary) Monte Carlo simulations with (N=10^5) families, 1000 days, yield:

where (b', g') are updated after one more child, assuming (p_n) based on their estimate (\hatR). the hardest interview 2

They compute expected marginal utility of an additional child: Given uniform prior (\lambda \sim U[0

where (k > 0) is a sensitivity parameter (here, (k=2)). Given uniform prior (\lambda \sim U[0.05

[ \Delta U = \mathbbE\left[ \fracb'g' - \fracbg \right] - \lambda \cdot 1 ]