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作者：Berrett, T. B.
作者单位：University of Warwick
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作者：Escobar-Bach, Mikael
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作者：Farewell, D. M.; Daniel, R. M.; Seaman, S. R.
作者单位：Cardiff University; MRC Biostatistics Unit; University of Cambridge
摘要：We offer a natural and extensible measure-theoretic treatment of missingness at random. Within the standard missing-data framework, we give a novel characterization of the observed data as a stopping-set sigma algebra. We demonstrate that the usual missingness-at-random conditions are equivalent to requiring particular stochastic processes to be adapted to a set-indexed filtration. These measurability conditions ensure the usual factorization of likelihood ratios. We illustrate how the theory ...
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作者：Ferraty, F.; Nagy, S.
作者单位：Universite de Toulouse; Charles University Prague
摘要：It is common to want to regress a scalar response on a random function. This paper presents results that advocate local linear regression based on a projection as a nonparametric approach to this problem. Our asymptotic results demonstrate that functional local linear regression outperforms its functional local constant counterpart. Beyond the estimation of the regression operator itself, local linear regression is also a useful tool for predicting the functional derivative of the regression o...
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作者：Cho, Hunyong; Holloway, Shannon T.; Couper, David J.; Kosorok, Michael R.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; North Carolina State University; University of North Carolina; University of North Carolina Chapel Hill
摘要：We propose a reinforcement learning method for estimating an optimal dynamic treatment regime for survival outcomes with dependent censoring. The estimator allows the failure time to be conditionally independent of censoring and dependent on the treatment decision times, supports a flexible number of treatment arms and treatment stages, and can maximize either the mean survival time or the survival probability at a certain time-point. The estimator is constructed using generalized random survi...
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作者：Henzi, Alexander; Ziegel, Johanna F.
作者单位：University of Bern
摘要：Probability forecasts for binary events play a central role in many applications. Their quality is commonly assessed with proper scoring rules, which assign forecasts numerical scores such that a correct forecast achieves a minimal expected score. In this paper, we construct e-values for testing the statistical significance of score differences of competing forecasts in sequential settings. E-values have been proposed as an alternative to p-values for hypothesis testing, and they can easily be...
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作者：Matsuda, T.; Strawderman, W. E.
作者单位：RIKEN; Rutgers University System; Rutgers University New Brunswick
摘要：We investigate estimation of a normal mean matrix under the matrix quadratic loss. Improved estimation under the matrix quadratic loss implies improved estimation of any linear combination of the columns under the quadratic loss. First, an unbiased estimate of risk is derived and the Efron-Morris estimator is shown to be minimax. Next, a notion of matrix superharmonicity for matrix-variate functions is introduced and shown to have properties analogous to those of the usual superharmonic functi...
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作者：Schrab, A.; Jitkrittum, W.; Szabo, Z.; Sejdinovic, D.; Gretton, A.
作者单位：University of London; University College London; Alphabet Inc.; Google Incorporated; University of London; London School Economics & Political Science; University of Oxford; University of London; University College London
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作者：Li, Wei
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作者：Benard, Clement; Da Veiga, Sebastien; Scornet, Erwan
作者单位：Safran S.A.; Institut Polytechnique de Paris; Ecole Polytechnique; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI)
摘要：Variable importance measures are the main tools used to analyse the black-box mechanisms of random forests. Although the mean decrease accuracy is widely accepted as the most efficient variable importance measure for random forests, little is known about its statistical properties. In fact, the definition of mean decrease accuracy varies across the main random forest software. In this article, our objective is to rigorously analyse the behaviour of the main mean decrease accuracy implementatio...
