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作者：Ait-Sahalia, Yacine; Xiu, Dacheng
作者单位：Princeton University; National Bureau of Economic Research; University of Chicago
摘要：We develop the necessary methodology to conduct principal component analysis at high frequency. We construct estimators of realized eigenvalues, eigenvectors, and principal components, and provide the asymptotic distribution of these estimators. Empirically, we study the high-frequency covariance structure of the constituents of the S&P 100 Index using as little as one week of high-frequency data at a time, and examines whether it is compatible with the evidence accumulated over decades of low...
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作者：Di Marzio, Marco; Panzera, Agnese; Taylor, Charles C.
作者单位：G d'Annunzio University of Chieti-Pescara; University of Florence; University of Leeds
摘要：Regression of data represented as points on a hypersphere has traditionally been treated using parametric families of transformations that include the simple rigid rotation as an important, special case. On the other hand, nonparametric methods have generally focused on modeling a scalar response through a spherical predictor by representing the regression function as a polynomial, leading to component-wise estimation of a spherical response. We propose a very flexible, simple regression model...
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作者：Wang, Yifei; Tancredi, Daniel J.; Miglioretti, Diana L.
作者单位：University of California System; University of California Davis; University of California System; University of California San Francisco
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作者：Wong, Raymond K. W.; Li, Yehua; Zhu, Zhengyuan
作者单位：Texas A&M University System; Texas A&M University College Station; University of California System; University of California Riverside; Iowa State University; Iowa State University
摘要：We investigate a class of partially linear functional additive models (PLFAM) that predicts a scalar response by both parametric effects of a multivariate predictor and nonparametric effects of a multivariate functional predictor. We jointly model multiple functional predictors that are cross-correlated using multivariate functional principal component analysis (mFPCA), and model the nonparametric effects of the principal component scores as additive components in the PLFAM. To address the hig...
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作者：Yauck, Mamadou; Rivest, Louis-Paul; Rothman, Greg
作者单位：Laval University
摘要：This work is concerned with the analysis of marketing data on the activation of applications (apps) on mobile devices. Each application has a hashed identification number that is specific to the device on which it has been installed. This number can be registered by a platform at each activation of the application. Activations on the same device are linked together using the identification number. By focusing on activations that took place at a business location, one can create a capture-recap...
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作者：Guerrier, Stephane; Dupuis-Lozeron, Elise; Ma, Yanyuan; Victoria-Feser, Maria-Pia
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; University of Geneva
摘要：Along with the ever increasing data size and model complexity, an important challenge frequently encountered in constructing new estimators or in implementing a classical one such as the maximum likelihood estimator, is the computational aspect of the estimation procedure. To carry out estimation, approximate methods such as pseudo-likelihood functions or approximated estimating equations are increasingly used in practice as these methods are typically easier to implement numerically although ...
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作者：Li, Li; Jara, Alejandro; Jose Garcia-Zattera, Maria; Hanson, Timothy E.
作者单位：University of New Mexico; Pontificia Universidad Catolica de Chile; Medtronic
摘要：Motivated by data gathered in an oral health study, we propose a Bayesian nonparametric approach for population-averaged modeling of correlated time-to-event data, when the responses can only be determined to lie in an interval obtained from a sequence of examination times and the determination of the occurrence of the event is subject to misclassification. The joint model for the true, unobserved time-to-event data is defined semiparametrically; proportional hazards, proportional odds, and ac...
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作者：Ding, Peng; Feller, Avi; Miratrix, Luke
作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley; Harvard University
摘要：Understanding and characterizing treatment effect variation in randomized experiments has become essential for going beyond the black box of the average treatment effect. Nonetheless, traditional statistical approaches often ignore or assume away such variation. In the context of randomized experiments, this article proposes a framework for decomposing overall treatment effect variation into a systematic component explained by observed covariates and a remaining idiosyncratic component. Our fr...
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作者：Mak, Simon; Wu, C. F. Jeff
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作者：Steingrimsson, Jon Arni; Diao, Liqun; Strawderman, Robert L.
作者单位：Brown University; University of Waterloo; University of Rochester
摘要：This article proposes a novel paradigm for building regression trees and ensemble learning in survival analysis. Generalizations of the classification and regression trees (CART) and random forests (RF) algorithms for general loss functions, and in the latter case more general bootstrap procedures, are both introduced. These results, in combination with an extension of the theory of censoring unbiased transformations (CUTs) applicable to loss functions, underpin the development of two new clas...
