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Titlebook: Exploring Research Frontiers in Contemporary Statistics and Econometrics; A Festschrift for Lé Ingrid Van Keilegom,Paul W. Wilson Book 2012

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Gerhard A. Holzapfel,Ray W. Ogdenstries and across different regions (coastal, central and western). We do so by performing a bootstrap-based analysis of group efficiencies (weighted and non-weighted), estimating and comparing densities of efficiency distributions, and conducting a bootstrapped truncated regression analysis. We fin
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https://doi.org/10.1007/978-94-015-8690-0r. The measurement error is assumed to be an additive normal random variable on the input variable, but its variance is unknown. The estimator is a modification of the .-frontier, which necessitates the computation of a consistent estimator of the conditional survival function of the input variable
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Composites for Marine Applications,l production literature and in the complementary literature on productive efficiency. We point out why panel data are needed to measure productive efficiency and innovation and thus link the two strands of literatures. We provide a discussion on the various estimators used in the two literatures, fo
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https://doi.org/10.1007/978-3-7091-0939-7nsoring, whereas . is completely observed. Let .(.) be a conditional location function of . given . = .. In this paper we assume that .( ⋅) belongs to some parametric class . and we propose a new method for estimating the true unknown value θ.. The method is based on nonparametric imputation for the
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https://doi.org/10.1007/978-94-010-9504-4he set . (or equivalently, the boundary function .) based on a set of observations laid on .. Then one may think of building the convex-hull of the observations to estimate the set ., and the corresponding estimator of the boundary function . is given by the roof of the constructed convex-hull. In t
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Mechanics of Elastic Biomoleculesusen and van den Broeck (Int. Econ. Rev. 18:435–444, 1997), and Battese and Cora (Aust. J. Agr. Econ. 21:169–179, 1977), researchers have often found that the residuals estimated from these models displayed skewness in the wrong direction. In such cases applied researchers were faced with two main a
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Vibrations of X-Braced Multi-Story Frames,ters can achieve root-. consistency. The requirement of under-smoothing may result, as we show, from inefficient estimation methods or technical difficulties. Xia et al. (J. Roy. Statist. Soc. B. 64:363–410, 2002) proposed an adaptive method for the multiple-index model, called MAVE. In this chapter
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