This report presents a Bayesian version of empirical orthogonal functions (EOFs) and thereby overcomes a difficulty with the classical version of these functions when an environmental process is autocorrelated as most are. The approach partitions the spatial variation into long and short scale variation, the latter including measurement errors. The most general version of our results incorporat...

Elicitation is the study of statistics or properties which are computable via empirical risk minimization. While several recent papers have approached the general question of which properties are elicitable, we suggest that this is the wrong question—all properties are elicitable by first eliciting the entire distribution or data set, and thus the important question is how elicitable. Specifica...

Using satellite-observed Normalized Difference Vegetation Index (NDVI) data and Rotated Empirical Orthogonal Function (REOF) method, we analyzed the spatio-temporal variation of vegetation during growing seasons from May to September in the Three-River Source Region, alpine meadow in the QinghaiTibetan Plateau from 1982 to 2006. We found that NDVI in the centre and east of the region, where the...

We prove an oracle inequality for generic regularized empirical risk minimization algorithms learning from α-mixing processes. To illustrate this oracle inequality, we use it to derive learning rates for some learning methods including least squares SVMs. Since the proof of the oracle inequality uses recent localization ideas developed for independent and identically distributed (i.i.d.) proces...

The rotational barrier about the C S bond in fluorocarbonylsulfenyl chloride [FC(0)SC1] is investigated using the C N D O method. The results confirm the existence of planar eis and trans conformers and the higher stability of the latter, as suggested by previous vibrational results. The valence force constants in FC(0)SC1 were also calculated and the values obtained compare favourably with res...

It has been recently shown that, under the margin (or low noise) assumption, there exist classifiers attaining fast rates of convergence of the excess Bayes risk, that is, rates faster than n−1/2. The work on this subject has suggested the following two conjectures: (i) the best achievable fast rate is of the order n−1, and (ii) the plug-in classifiers generally converge more slowly than the cl...

We study large-scale classification problems in changing environments where a small part of the dataset is modified, and the effect of the data modification must be quickly incorporated into the classifier. When the entire dataset is large, even if the amount of the data modification is fairly small, the computational cost of re-training the classifier would be prohibitively large. In this pape...

A large volume of empirical research has accumulated on the relationship between religion/spirituality (R/S) and health since the year 2000, much of it involving older adults. The purpose of this article is to discuss how this body of existing research findings has important messages or important new insights for gerontologists; clinicians in medicine, psychiatry, and psychology; sociologists; ...

We study the recovery of sparse signals from underdetermined linear measurements when a potentially erroneous support estimate is available. Our results are twofold. First, we derive necessary and sufficient conditions for signal recovery from compressively sampled measurements using weighted l1norm minimization. These conditions, which depend on the choice of weights as well as the size and ac...

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