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作者：Brunel, Nicolas J-B.; Clairon, Quentin; D'Alche-Buc, Florence
作者单位：Universite Paris Saclay; Ecole Nationale Superieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE); INRAE; INRAE; Universite Paris Saclay; Universite Paris Saclay; Universite Paris Saclay; Universite Paris Saclay
摘要：Differential equations are commonly used to model dynamical deterministic systems in applications. When statistical parameter estimation is required to calibrate theoretical models to data, classical statistical estimators are often confronted to complex and potentially ill-posed optimization problem. As a consequence, alternative estimators to classical parametric estimators are needed for obtaining reliable estimates. We propose a gradient matching approach for the estimation of parametric O...
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作者：Dette, Holger; Van Hecke, Ria; Volgushev, Stanislav
作者单位：Ruhr University Bochum
摘要：In a recent article, Noh, El Ghouch, and Bouezmarni proposed a new semiparametric estimate of a regression function with a multivariate predictor, which is based on a specification of the dependence structure between the predictor and the response by means of a parametric copula. This comment investigates the effect which occurs under misspecification of the parametric model. We demonstrate by means of several examples that even for a one or two-dimensional predictor the error caused by a wron...
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作者：Xu, Chen; Chen, Jiahua
作者单位：University of British Columbia
摘要：Feature selection is fundamental for modeling the high-dimensional data, where the number of features can be huge and much larger than the sample size. Since the feature space is so large, many traditional procedures become numerically infeasible. It is hence essential to first remove most apparently noninfluential features before any elaborative analysis. Recently, several procedures have been developed for this purpose, which include the sure-independent-screening (SIS) as a widely used tech...
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作者：Chen, Kun; Chan, Kung-Sik; Stenseth, Nils Chr.
作者单位：University of Connecticut; University of Iowa; University of Oslo
摘要：The problem of reconstructing the source-sink dynamics arises in many biological systems. Our research is motivated by marine applications where newborns are passively dispersed by ocean currents from several potential spawning sources to settle in various nursery regions that collectively constitute the sink. The reconstruction of the sparse source-sink linkage pattern, that is, to identify which sources contribute to which regions in the sink, is a challenging task in marine ecology. We deri...
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作者：Crawford, Forrest W.; Minin, Vladimir N.; Suchard, Marc A.
作者单位：Yale University; University of Washington; University of Washington Seattle; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
摘要：Birth-death processes (BDPs) are continuous-time Markov chains that track the number of particles in a system over time. While widely used in population biology, genetics, and ecology, statistical inference of the instantaneous particle birth and death rates remains largely limited to restrictive linear BDPs in which per-particle birth and death rates are constant. Researchers often observe the number of particles at discrete times, necessitating data augmentation procedures such as expectatio...
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作者：Zheng, Shuzhuan; Yang, Lijian; Haerdle, Wolfgang K.
作者单位：Michigan State University; Soochow University - China; Humboldt University of Berlin; Singapore Management University
摘要：Functional data analysis (FDA) has become an important area of statistics research in the recent decade, yet a smooth simultaneous confidence corridor (SCC) does not exist in the literature for the mean function of sparse functional data. SCC is a powerful tool for making statistical inference on an entire unknown function, nonetheless classic Hungarian embedding techniques for establishing asymptotic correctness of SCC completely fail for sparse functional data. We propose a local linear SCC ...
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作者：Ing, Ching-Kang; Yang, Chiao-Yi
作者单位：Academia Sinica - Taiwan; National Taiwan University
摘要：Let observations y(1),..., y(n) be generated from a first-order autoregressive (AR) model with positive errors. In both the stationary and unit root cases, we derive moment bounds and limiting distributions of an extreme value estimator, rho(n), of the AR coefficient. These results enable us to provide asymptotic expressions for the mean squared error (MSE) of rho n and the mean squared prediction error (MSPE) of the corresponding predictor, y(n+1), of y(n+1) Based on these expressions, we com...
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作者：Liu, Jingyuan; Li, Runze; Wu, Rongling
作者单位：Xiamen University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health
摘要：This article is concerned with feature screening and variable selection for varying coefficient models with ultrahigh-dimensional covariates. We propose a new feature screening procedure for these models based on conditional correlation coefficient. We systematically study the theoretical properties of the proposed procedure, and establish their sure screening property and the ranking consistency. To enhance the finite sample performance of the proposed procedure, we further develop an iterati...
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作者：Chan, Ngai Hang; Yau, Chun Yip; Zhang, Rong-Mao
作者单位：Chinese University of Hong Kong; Renmin University of China; Zhejiang University
摘要：Consider a structural break autoregressive (SBAR) process Y-1 = Sigma(m+1)(j=1) (sic)beta jT Yt-1 + sigma(Yt-1, ...,Yt-q)epsilon 1(sic) I(t(j-1) <= t < t(1) < ... < t(m) vertical bar 1 = n + 1, sigma (.) is a measurable function on R-q, and {epsilon(t)} are white noise with unit variance. In practice, the number of change-points m is usually assumed to be known and small, because a large m would involve a huge amount of computational burden for parameters estimation. By reformulating the probl...
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作者：Delaigle, Aurore; Hall, Peter
作者单位：University of Melbourne; University of California System; University of California Davis
摘要：Nonparametric estimation of a density from contaminated data is a difficult problem, for which convergence rates are notoriously slow. We introduce parametrically assisted nonparametric estimators which can dramatically improve on the performance of standard nonparametric estimators when the assumed model is close to the true density, without degrading much the quality of purely nonparametric estimators in other cases. We establish optimal convergence rates for our problem and discuss estimato...
