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作者：Benko, Michal; Haerdle, Wolfgang; Kneip, Alois
作者单位：Humboldt University of Berlin; University of Bonn
摘要：Functional principal component analysis (FPCA) based on the Karhunen-Loeve decomposition has been successfully applied in many applications, mainly for one sample problems. In this paper we consider common functional principal components for two sample problems. Our research is motivated not only by the theoretical challenge of this data situation, but also by the actual question of dynamics of implied volatility (IV) functions. For different maturities the log-returns of IVs are samples of (s...
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作者：Boysen, Leif; Kempe, Angela; Liebscher, Volkmar; Munk, Axel; Wittich, Olaf
作者单位：University of Gottingen; Helmholtz Association; Helmholtz-Center Munich - German Research Center for Environmental Health; Universitat Greifswald; Eindhoven University of Technology
摘要：We study the asymptotics for jump-penalized least squares regression aiming at approximating a regression function by piecewise constant functions. Besides conventional consistency and convergence rates of the estimates in L-2([0, 1)) our results cover other metrics like Skorokhod metric on the space of cadlag functions and uniform metrics on C([0, 1]). We will show that these estimators are in an adaptive sense rate optimal over certain classes of approximation spaces. Special cases are the c...
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作者：Meinshausen, Nicolai; Yu, Bin
作者单位：University of Oxford; University of California System; University of California Berkeley
摘要：The Lasso is an attractive technique for regularization and variable selection for high-dimensional data, where the number of predictor variables p(n) is potentially much larger than the number of samples n. However, it was recently discovered that the sparsity pattern of the Lasso estimator can only be asymptotically identical to the true sparsity pattern if the design matrix satisfies the so-called irrepresentable condition. The latter condition can easily be violated in the presence of high...
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作者：Osius, Gerhard
作者单位：University of Bremen; Leibniz Association; Leibniz Institute for Prevention Research & Epidemiology (BIPS)
摘要：Association models for a pair of random elements X and Y (e.g., vectors) are considered which specify the odds ratio function up to an unknown parameter theta. These models are shown to be semiparametric in the sense that they do not restrict the marginal distributions of X and Y. Inference for the odds ratio parameter theta may be obtained from sampling either Y conditionally on X or vice versa. Generalizing results from Prentice and Pyke, Weinberg and Wacholder and Scott and Wild, we show th...
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作者：Clarke, Sandy; Hall, Peter
作者单位：University of Melbourne
摘要：An important aspect of multiple hypothesis testing is controlling the significance level, or the level of Type I error. When the test statistics are not independent it can be particularly challenging to deal with this problem, without resorting to very conservative procedures. In this paper we show that, in the context of contemporary multiple testing problems, where the number of tests is often very large, the difficulties caused by dependence are less serious than in classical cases. This is...
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作者：Koul, Hira L.; Song, Weixing
作者单位：Michigan State University; Kansas State University
摘要：Lack-of-fit testing of a regression model with Berkson measurement error has not been discussed in the literature to date. To fill this void, we propose a class of tests based on minimized integrated square distances between nonparametric regression function estimator and the parametric model being fitted. We prove asymptotic normality of these test statistics under the null hypothesis and that of the corresponding minimum distance estimators under minimal conditions on the model being fitted....
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作者：Hjort, Nils Lid; Walker, Stephen G.
作者单位：University of Oslo; University of Kent
摘要：Polya trees fix partitions and use random probabilities in order to construct random probability measures. With quantile pyramids we instead fix probabilities and use random partitions. For nonparametric Bayesian inference we use a prior which supports piecewise linear quantile functions, based on the need to work with a finite set of partitions, yet we show that the limiting version of the prior exists. We also discuss and investigate an alternative model based on the so-called substitute lik...
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作者：Yang, Min; Stufken, John
作者单位：University of Missouri System; University of Missouri Columbia; University System of Georgia; University of Georgia
摘要：We propose a new approach for identifying the support points of a locally optimal design when the model is a nonlinear model. In contrast to the commonly used geometric approach, we use an approach based on algebraic tools. Considerations are restricted to models with two parameters, and the general results are applied to often used special cases, including logistic, probit, double exponential and double reciprocal models for binary data, a loglinear Poisson regression model for count data, an...
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作者：Fang, Fang; Hong, Quan; Shao, Jun
作者单位：Eli Lilly; Lilly Research Laboratories; University of Wisconsin System; University of Wisconsin Madison
摘要：Nonresponse is common in Surveys. When the response probability of a survey variable Y depends on Y through ail observed auxiliary categorical variable Z (i.e., the response probability of Y is conditionally independent of Y given Z), a simple method often used in practice is to use Z categories as imputation cells and construct estimators by imputing nonrespondents or reweighting respondents within each imputation cell. This simple method, however, is inefficient when some Z categories have s...
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作者：Wang, Dong; Chen, Song Xi
作者单位：University of Nebraska System; University of Nebraska Lincoln; Iowa State University; Peking University
摘要：We consider an empirical likelihood inference for parameters defined by general estimating equations when some components of the random observations are subject to missingness. As the nature of the estimating equations is wide-ranging, we propose a nonparametric imputation of the missing values from a kernel estimator of the conditional distribution of the missing variable given the always observable variable. The empirical likelihood is used to construct a profile likelihood for the parameter...
