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作者：McLatchie, Y.; Fong, E.; Frazier, D. T.; Knoblauch, J.
作者单位：University of London; University College London; University of Hong Kong; Monash University
摘要：We analyse the impact of using tempered likelihoods in the production of posterior predictions. While the choice of temperature has an impact on predictive performance in small samples, we formally show that in moderate-to-large samples, tempering does not impact posterior predictions.
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作者：Wu, Yinxiang; Kang, Hyunseung; Ye, Ting
作者单位：University of Washington; University of Washington Seattle; University of Wisconsin System; University of Wisconsin Madison
摘要：Multivariable Mendelian randomization uses genetic variants as instrumental variables to infer the direct effects of multiple exposures on an outcome. However, unlike univariable Mendelian randomization, multivariable Mendelian randomization often faces greater challenges with many weak instruments, which can lead to bias not necessarily toward zero and inflation of Type-I errors. In this work, we introduce a new asymptotic regime that allows exposures to have varying degrees of instrument str...
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作者：Zhang, Jeffrey; Lee, Junu
作者单位：University of Pennsylvania
摘要：In real-world studies, the collected confounders may suffer from measurement error. Although mismeasurement of confounders is typically unintentional (originating from sources such as human oversight or imprecise machinery), deliberate mismeasurement also occurs and is becoming increasingly more common. For example, in the 2020 U.S. census, noise was added to measurements to assuage privacy concerns. Sensitive variables such as income or age are often partially censored and are only known up t...
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作者：Gilbert, Brian; Ogburn, Elizabeth L.; Datta, Abhirup
作者单位：Johns Hopkins University
摘要：This article addresses the asymptotic performance of popular spatial regression estimators of the linear effect of an exposure on an outcome under spatial confounding, the presence of an unmeasured spatially structured variable influencing both the exposure and the outcome. We first show that the estimators from ordinary least squares and restricted spatial regression are asymptotically biased under spatial confounding. We then prove a novel result on the infill consistency of the generalized ...
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作者：Baddeley, A.; Davies, T. M.; Hazelton, M. L.
作者单位：Curtin University; University of Otago
摘要：The pair correlation function, or two-point correlation, of a spatial point process is a fundamental tool in spatial statistics and astrostatistics, measuring the strength of spatial dependence between points. Interest is focused on the behaviour of this function at short distances, but this is the region in which existing estimators can be particularly unreliable. We propose a new estimator of the pair correlation function based on techniques from stochastic geometry and kernel density estima...
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作者：Heng, J.; De Bortoli, V; Doucet, A.; Thornton, J.
作者单位：ESSEC Business School; Universite PSL; Ecole Normale Superieure (ENS); University of Oxford
摘要：We consider the problem of simulating diffusion bridges, which are diffusion processes that are conditioned to initialize and terminate at two given states. The simulation of diffusion bridges has applications in diverse scientific fields and plays a crucial role in the statistical inference of discretely observed diffusions. This is known to be a challenging problem that has received much attention in the last two decades. This article contributes to this rich body of literature by presenting...
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作者：Xu, Jiazhen; Wood, Andrew T. A.; Zou, Tao
作者单位：Australian National University
摘要：Functional data analysis offers a diverse toolkit of statistical methods tailored to analysing samples of real-valued random functions. Recently, samples of time-varying random objects, such as time-varying networks, have been increasingly encountered in data analysis. These data structures represent elements within general metric spaces that lack local or global linear structures, rendering traditional functional data analysis methods inapplicable. Moreover, the existing methodology for time-...
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作者：Zhang, Chao; Geng, Zhi; Li, Wei; Ding, Peng
作者单位：Beijing Technology & Business University; Renmin University of China; Renmin University of China; University of California System; University of California Berkeley
摘要：Although the existing causal inference literature focuses on the forward-looking perspective by estimating effects of causes, the backward-looking perspective can provide insights into causes of effects. In backward-looking causal inference, the probability of necessity measures the probability that a certain event is caused by the treatment, given the observed treatment and outcome. Most existing results focus on binary outcomes. Motivated by applications with ordinal outcomes, we propose a g...
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作者：Palasciano, H. A.; Knight, M., I; Nason, G. P.
作者单位：Imperial College London; University of York - UK
摘要：This article introduces the class of continuous-time locally stationary wavelet processes. Continuous-time models enable us to properly provide scale-based time series models for irregularly spaced observations for the first time, while also permitting a spectral representation of the process over a continuous range of scales. We derive results for both the theoretical setting, where we assume access to the entire process sample path, and a more practical one, which develops methods for estima...
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作者：Sjolander, A.; Hagg, S.
作者单位：Karolinska Institutet
摘要：A common aim of empirical research is to regress an outcome on a set of covariates, when some covariates are subject to missingness. If the probability of missingness is conditionally independent of the outcome, given the covariates, then a complete-case analysis is unbiased for parameters conditional on covariates. We derive all testable constraints that such outcome-independent missingness not at random implies on the observed data distribution, for settings where both the outcome and covari...
