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作者：Zhang, Chenlin; Zhou, Ling; Guo, Bin; Lin, Huazhen
作者单位：Southwestern University of Finance & Economics - China; Southwestern University of Finance & Economics - China
摘要：We develop a Spatial Effect Detection Regression (SEDR) model to capture the nonlinear and irregular effects of high-dimensional spatio-temporal predictors on a scalar outcome. Specifically, we assume that both the component and the coefficient functions in the SEDR are unknown smooth functions of location and time. This allows us to leverage spatially and temporally correlated information, transforming the curse of dimensionality into a blessing, as confirmed by our theoretical and numerical ...
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作者：Shen, Xinwei; Meinshausen, Nicolai
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：Distributional regression aims to estimate the full conditional distribution of a target variable, given covariates. Popular methods include linear and tree ensemble based quantile regression. We propose a neural network- based distributional regression methodology called 'engression'. An engression model is generative in the sense that we can sample from the fitted conditional distribution and is also suitable for high-dimensional outcomes. Furthermore, we find that modelling the conditional ...
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作者：Kiriliouk, Anna; Lee, Jeongjin; Segers, Johan
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作者：Agniel, Denis; Parast, Layla
作者单位：RAND Corporation; Rand Health; University of Texas System; University of Texas Austin
摘要：The development of statistical methods to evaluate surrogate markers is an active area of research. In many clinical settings, the surrogate marker is not simply a single measurement but is instead a longitudinal trajectory of measurements over time, e.g. fasting plasma glucose measured every 6 months for 3 years. In general, available methods developed for the single-surrogate setting cannot accommodate a longitudinal surrogate marker. Furthermore, many of the methods have not been developed ...
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作者：Cabral, Rafael; Bolin, David; Rue, Havard
作者单位：King Abdullah University of Science & Technology
摘要：Model checking is essential to evaluate the adequacy of statistical models and the validity of inferences drawn from them. Particularly, hierarchical models such as latent Gaussian models (LGMs) pose unique challenges as it is difficult to check assumptions on the latent parameters. Diagnostic statistics are often used to quantify the degree to which a model fit deviates from the observed data. We construct diagnostic statistics by (a) defining an alternative model with relaxed assumptions and...
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作者：Kiriliouk, Anna; Lee, Jeongjin; Segers, Johan
作者单位：University of Namur; Universite Catholique Louvain
摘要：Regular vine sequences permit the organization of variables in a random vector along a sequence of trees. Vine-based dependence models have become greatly popular as a way to combine arbitrary bivariate copulas into higher-dimensional ones, offering flexibility, parsimony, and tractability. In this project, we use regular vine sequences to decompose and construct the exponent measure density of a multivariate extreme value distribution, or, equivalently, the tail copula density. Although these...
