The nonparametric Kiefer-Weiss problem is solved by deriving an optimal stopping policy based on a two-dimensional statistic (likelihood ratio plus expected remaining sample size) whose randomization rule maps the likelihood ratio to an integer sample size.
W., & Goodman, L
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Compares Markov chain, beta regression and multinomial logistic regression for loan default term-structures on mortgage data and reports successive outperformance plus new diagnostics.
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The Nonparametric Kiefer-Weiss Problem
The nonparametric Kiefer-Weiss problem is solved by deriving an optimal stopping policy based on a two-dimensional statistic (likelihood ratio plus expected remaining sample size) whose randomization rule maps the likelihood ratio to an integer sample size.
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Modelling the term-structure of default risk under IFRS 9 within a multistate regression framework
Compares Markov chain, beta regression and multinomial logistic regression for loan default term-structures on mortgage data and reports successive outperformance plus new diagnostics.