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作者：Fattorini, L.; Marcheselli, M.; Pisani, C.; Pratelli, L.
作者单位：University of Siena
摘要：We analyse the estimation of values of a survey variable throughout a continuum of points in a study area when a sample of points is selected by a probabilistic sampling scheme. At each point, the value is estimated using an inverse distance weighting interpolator, and maps of the survey variable can be obtained. We investigate the design-based asymptotic properties of the interpolator when the study area remains fixed and the number of sampled points approaches infinity, and we derive conditi...
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作者：Wang, Yaping; Yang, Jianfeng; Xu, Hongquan
作者单位：Peking University; Nankai University; University of California System; University of California Los Angeles
摘要：Maximin distance designs and orthogonal designs are widely used in computer and physical experiments. We characterize a broad class of maximin distance designs by establishing new bounds on the minimum intersite distance for mirror-symmetric and general U-type designs. We showthat maximin distance designs and orthogonal designs are closely related and coincide under some conditions.
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作者：Cronie, O.; van Lieshout, M. N. M.
作者单位：Umea University; University of Twente
摘要：We propose a new bandwidth selection method for kernel estimators of spatial point process intensity functions. The method is based on an optimality criterion motivated by the Campbell formula applied to the reciprocal intensity function. The new method is fully nonparametric, does not require knowledge of higher-order moments, and is not restricted to a specific class of point process. Our approach is computationally straightforward and does not require numerical approximation of integrals.
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作者：Kong, Xin-Bing; Xu, Shao-Jun; Zhou, Wang
作者单位：Nanjing Audit University; Shanghai University of Finance & Economics; National University of Singapore
摘要：Volatility functionals are widely used in financial econometrics. In the literature, they are estimated with realized volatility functionals using high-frequency data. In this paper we introduce a nonparametric local bootstrap method that resamples the high-frequency returns with replacement in local windows shrinking to zero. While the block bootstrap in time series (Hall et al., 1995) aims to reduce correlation, the local bootstrap is intended to eliminate the heterogeneity of volatility. We...
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作者：Fokianos, K.; Pitsillou, M.
作者单位：University of Cyprus
摘要：We introduce the matrix multivariate auto-distance covariance and correlation functions for time series, discuss their interpretation and develop consistent estimators for practical implementation. We also develop a test of the independent and identically distributed hypothesis for multivariate time series data and show that it performs better than the multivariate Ljung-Box test. We discuss computational aspects and present a data example to illustrate the method.
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作者：Li, Wentao; Fearnhead, Paul
作者单位：Newcastle University - UK; Lancaster University
摘要：We present asymptotic results for the regression-adjusted version of approximate Bayesian computation introduced by Beaumont et al. (2002). We show that for an appropriate choice of the bandwidth, regression adjustment will lead to a posterior that, asymptotically, correctly quantifies uncertainty. Furthermore, for such a choice of bandwidth we can implement an importance sampling algorithm to sample from the posterior whose acceptance probability tends to unity as the data sample size increas...
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作者：Jung, Sungkyu; Lee, Myung Hee; Ahn, Jeongyoun
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Cornell University; Weill Cornell Medicine; University System of Georgia; University of Georgia
摘要：We consider how many components to retain in principal component analysis when the dimension is much higher than the number of observations. To estimate the number of components, we propose to sequentially test skewness of the squared lengths of residual scores that are obtained by removing leading principal components. The residual lengths are asymptotically left-skewed if all principal components with diverging variances are removed, and right-skewed otherwise. The proposed estimator is show...
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作者：Li, Wentao; Fearnhead, Paul
作者单位：Newcastle University - UK; Lancaster University
摘要：Many statistical applications involve models for which it is difficult to evaluate the likelihood, but from which it is relatively easy to sample. Approximate Bayesian computation is a likelihood-free method for implementing Bayesian inference in such cases. We present results on the asymptotic variance of estimators obtained using approximate Bayesian computation in a large data limit. Our key assumption is that the data are summarized by a fixed-dimensional summary statistic that obeys a cen...
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作者：Yu, C.; Hoff, P. D.
作者单位：University of Washington; University of Washington Seattle; Duke University
摘要：Commonly used interval procedures for multigroup data attain their nominal coverage rates across a population of groups on average, but their actual coverage rate for a given group will be above or below the nominal rate, depending on the group mean. While correct coverage for a given group can be achieved with a standard t-interval, this approach is not adaptive to the available information about the distribution of group-specific means. In this article we construct confidence intervals that ...
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作者：Avella-Medina, Marco; Battey, Heather S.; Fan, Jianqing; Li, Quefeng
作者单位：Massachusetts Institute of Technology (MIT); Imperial College London; Princeton University; University of North Carolina; University of North Carolina Chapel Hill
摘要：High-dimensional data are often most plausibly generated from distributions with complex structure and leptokurtosis in some or all components. Covariance and precision matrices provide a useful summary of such structure, yet the performance of popular matrix estimators typically hinges upon a sub-Gaussianity assumption. This paper presents robust matrix estimators whose performance is guaranteed for a much richer class of distributions. The proposed estimators, under a bounded fourth moment a...
