Papers › Accelerating the pool-adjacent-violators algorithm for isotonic distributional regression
Accelerating the pool-adjacent-violators algorithm for isotonic distributional regression
Alexander Henzi, Alexandre Moesching, Lutz Duembgen
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In the context of estimating stochastically ordered distribution functions, the pool-adjacent-violators algorithm (PAVA) can be modified such that the computation times are reduced substantially. This is achieved by studying the dependence of antitonic weighted least squares fits on the response vector to be approximated.
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