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作者：Lu, Zudi; Tjostheim, Dag
作者单位：University of Southampton; University of Southampton; University of Bergen
摘要：Nonparametric estimation of probability density functions, both marginal and joint densities, is a very useful tool in statistics. The kernel method is popular and applicable to dependent data, including time series and spatial data. But at least for the joint density, one has had to assume that data are observed at regular time intervals or on a regular grid in space. Though this is not very restrictive in the time series case, it often is in the spatial case. In fact, to a large degree it ha...
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作者：Graham, Daniel J.; McCoy, Emma J.; Stephens, David A.
作者单位：Imperial College London; Imperial College London; McGill University
摘要：Road network capacity expansions are frequently proposed as solutions to urban traffic congestion but are controversial because it is thought that they can directly induce growth in traffic volumes. This article quantifies causal effects of road network capacity expansions on aggregate urban traffic volume and density in U.S. cities using a mixed model propensity score (PS) estimator. The motivation for this approach is that we seek to estimate a dose-response relationship between capacity and...
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作者：Tian, Lu; Alizadeh, Ash A.; Gentles, Andrew J.; Tibshirani, Robert
作者单位：Stanford University; Stanford University; Stanford University; Stanford University
摘要：We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. We propose a simple method for modeling interactions between the treatment and covariates. The idea is to modify the covariate in a simple way, and then fit a standard model using the modified covariates and no main effects. We show that coupled with an efficiency augmentation procedure, this method produces...
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作者：Wang, Fangpo; Gelfand, Alan E.
作者单位：Adobe Systems Inc.; Duke University
摘要：Directional data naturally arise in many scientific fields, such as oceanography (wave direction), meteorology (wind direction), and biology (animal movement direction). Our contribution is to develop a fully model-based approach to capture structured spatial dependence for modeling directional data at different spatial locations. We build a projected Gaussian spatial process, induced from an inline bivariate Gaussian spatial process. We discuss the properties of the projected Gaussian process...
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作者：Jung, Yoonsuh; Huang, Jianhua Z.; Hu, Jianhua
作者单位：University of Waikato; Texas A&M University System; Texas A&M University College Station; Capital University of Economics & Business; University of Texas System; UTMD Anderson Cancer Center
摘要：In genome-wide association studies, the primary task is to detect biomarkers in the form of single nucleotide polymorphisms (SNPs) that have nontrivial associations with a disease phenotype and some other important clinical/environmental factors. However, the extremely large number of SNPs compared to the sample size inhibits application of classical methods such as the multiple logistic regression. Currently, the most commonly used approach is still to analyze one SNP at a time. In this artic...
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作者：Plumlee, Matthew
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：Random field models have been widely employed to develop a predictor of an expensive function based on observations from an experiment. The traditional framework for developing a predictor with random field models can fail due to the computational burden it requires. This problem is often seen in cases where the input of the expensive function is high dimensional. While many previous works have focused on developing an approximative predictor to resolve these issues, this article investigates ...
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作者：Stroud, Jonathan R.; Johannes, Michael S.
作者单位：George Washington University; Columbia University
摘要：This article estimates models of high-frequency index futures returns using around-the-clock 5-min returns that incorporate the following key features: multiple persistent stochastic volatility factors, jumps in prices and volatilities, seasonal components capturing time of the day patterns, correlations between return and volatility shocks, and announcement effects. We develop an integrated MCMC approach to estimate interday and intraday parameters and states using high-frequency data without...
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作者：Song, Xiao; Wang, Ching-Yun
作者单位：University System of Georgia; University of Georgia; Fred Hutchinson Cancer Center
摘要：In biomedical studies, covariates with measurement error may occur in survival data. Existing approaches mostly require certain replications on the error-contaminated covariates, which may not be available in the data. In this article, we develop a simple nonparametric correction approach for estimation of the regression parameters in the proportional hazards model using a subset of the sample where instrumental variables are observed. The instrumental variables are related to the covariates t...
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作者：Abadie, Alberto; Imbens, Guido W.; Zheng, Fanyin
作者单位：Harvard University; National Bureau of Economic Research; Stanford University; Harvard University
摘要：Following the work by Eicker, Huber, and White it is common in empirical work to report standard errors that are robust against general misspecification. In a regression setting, these standard errors are valid for the parameter that minimizes the squared difference between the conditional expectation and a linear approximation, averaged over the population distribution of the covariates. Here, we discuss an alternative parameter that corresponds to the approximation to the conditional expecta...
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作者：Ning, Jing; Qin, Jing; Shen, Yu
作者单位：University of Texas System; UTMD Anderson Cancer Center; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
摘要：The semiparametric accelerated failure time (AFT) model is one of the most popular models for analyzing time-to-event outcomes. One appealing feature of the AFT model is that the observed failure time data can be transformed to identically independent distributed random variables without covariate effects. We describe a class of estimating equations based on the score functions for the transformed data, which are derived from the full likelihood function under commonly used semiparametric mode...
