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作者：Huang, Yijian; Sanda, Martin G.
作者单位：Emory University; Emory University
摘要：Multiple biomarkers are often combined to improve disease diagnosis. The uniformly optimal combination, that is, with respect to all reasonable performance metrics, unfortunately requires excessive distributional modeling, to which the estimation can be sensitive. An alternative strategy is rather to pursue local optimality with respect to a specific performance metric. Nevertheless, existing methods may not target clinical utility of the intended medical test, which usually needs to operate a...
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作者：Chernozhuokov, Victor; Chetverikov, Denis; Kato, Kengo; Koike, Yuta
作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); University of California System; University of California Los Angeles; Cornell University; University of Tokyo; University of Tokyo
摘要：This paper deals with the Gaussian and bootstrap approximations to the distribution of the max statistic in high dimensions. This statistic takes the form of the maximum over components of the sum of independent random vectors and its distribution plays a key role in many high-dimensional estimation and testing problems. Using a novel iterative randomized Lindeberg method, the paper derives new bounds for the distributional approximation errors. These new bounds substantially improve upon exis...
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作者：Velasco, Carlos
作者单位：Universidad Carlos III de Madrid
摘要：We propose new estimation methods for time series models, possibly noncausal and/or noninvertible, using serial dependence information from the characteristic function of model residuals. This allows to impose the i.i.d. or martingale difference assumptions on the model errors to identify the unknown location of the roots of the lag polynomials for ARMA models without resorting to higher order moments or distributional assumptions. We consider generalized spectral density and cumulative distri...
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作者：Chen, Guanzhou; Tang, Boxin
作者单位：Simon Fraser University
摘要：Space-filling designs based on orthogonal arrays are attractive for computer experiments for they can be easily generated with desirable low-dimensional stratification properties. Nonetheless, it is not very clear how they behave and how to construct good such designs under other space-filling criteria. In this paper, we justify orthogonal array-based designs under a broad class of space-filling criteria, which include commonly used distance-, orthogonality- and discrepancy-based measures. To ...
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作者：Rytgaard, Helene C.; Gerds, Thomas A.; van der Laan, Mark J.
作者单位：University of Copenhagen; University of California System; University of California Berkeley; University of California System; University of California Berkeley
摘要：This paper generalizes the targeted minimum loss-based estimation (TMLE) framework to allow for estimating the effects of time-varying interventions in settings where both interventions, covariates, and outcome can happen at subject-specific time-points on an arbitrarily fine time-scale. TMLE is a general template for constructing asymptotically linear substitution estimators for smooth low-dimensional parameters in infinite-dimensional models. Existing longitudinal TMLE methods are developed ...
