-
作者：Belomestny, Denis
作者单位：Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics
摘要：We consider the problem of estimating the fractional order of a Levy process from low frequency historical and options data. An estimation methodology is developed which allows us to treat both estimation and calibration problems in a unified way. The corresponding procedure consists of two steps: the estimation of a conditional characteristic function and the weighted least squares estimation of the fractional order in spectral domain. While the second step is identical for both calibration a...
-
作者：El Karoui, Noureddine
作者单位：University of California System; University of California Berkeley
摘要：We place Ourselves in the setting of high-dimensional statistical inference where the number of variables p in a dataset of interest is of the same order of magnitude as the number of observations n. We consider the spectrum of certain kernel random matrices, in particular n x n matrices whose (i, j)th entry is f(X-i' X-j/p) or f(vertical bar vertical bar X-i - X-j vertical bar vertical bar(2)/p) where p is the dimension of the data, and X-i are independent data vectors. Here f is assumed to b...
-
作者：Cai, T. Tony; Jin, Jiashun
作者单位：University of Pennsylvania; Carnegie Mellon University
摘要：An important estimation problem that is closely related to large-scale multiple testing is that of estimating the null density and the proportion of nonnull effects. A few estimators have been introduced in the literature; however, several important problems, including the evaluation of the minimax rate of convergence and the construction of rate-optimal estimators, remain open. In this paper, we consider optimal estimation of the null density and the proportion of nonnull effects. Both minima...
-
作者：Groeneboom, Piet; Jongbloed, Geurt; Witte, Birgit I.
作者单位：Delft University of Technology
摘要：We consider the problem of estimating the distribution function, the density and the hazard rate of the (unobservable.) event time in the current status model. A well studied and natural nonparametric estimator for the distribution function in this model is the nonparametric maximum likelihood estimator (MILE). We study two alternative methods for the estimation of the distribution function, assuming some smoothness of the event time distribution. The first estimator is based oil a maximum smo...
-
作者：Mijatovic, Aleksandar; Schneider, Paul
作者单位：Imperial College London; University of Warwick
摘要：This paper studies an approximation method for the log-likelihood function of a nonlinear diffusion process using the bridge of the diffusion. The main result (Theorem 1) shows that this approximation converges uniformly to the unknown likelihood function and can therefore be used efficiently with any algorithm for sampling from the law of the bridge. We also introduce an expected maximum likelihood (EML) algorithm for inferring the parameters of discretely observed diffusion processes. The ap...
-
作者：Arlot, Sylvain; Blanchard, Gilles; Roquain, Etienne
作者单位：Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Information Sciences & Technologies (INS2I); Inria; Universite PSL; Ecole Normale Superieure (ENS); Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Sorbonne Universite; Universite Paris Cite
摘要：We Study generalized bootstrap confidence regions for the mean of a random vector whose coordinates have an unknown dependency structure. The random vector is supposed to be either Gaussian or to have a symmetric and bounded distribution. The dimensionality of the vector can possibly be much larger than the number of observations and we focus on a nonasymptotic control of the confidence level, following ideas inspired by recent results in learning theory. We consider two approaches, the first ...
-
作者：Liao, Yuan; Jiang, Wenxin
作者单位：Northwestern University
摘要：This paper presents a study of the large-sample behavior of the posterior distribution of a structural parameter which is partially identified by moment inequalities. The posterior density is derived based on the limited information likelihood. The posterior distribution converges to zero exponentially fast on any delta-contraction Outside the identified region. Inside, if is bounded below by a positive constant if the identified region is assumed to have a nonempty interior. Our simulation ev...
-
作者：Lahiri, S. N.
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：In this paper, we derive valid Edgeworth expansions for studentized versions of a large class of statistics when the data are generated by a strongly mixing process. Under dependence, the asymptotic variance of such a statistic is given by an infinite series of lag-covariances, and therefore, studentizing factors (i.e., estimators of the asymptotic standard error) typically involve an increasing number, say, l of lag-covariance estimators, which are themselves quadratic functions of the observ...
