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作者：Nason, Guy
作者单位：University of Bristol
摘要：Many time series are not second order stationary and it is not appropriate to analyse them by using methods designed for stationary series. The paper introduces a new test for second-order stationarity that detects kinds of departures from stationarity that are different from those based on Fourier methods. The new test is also computationally fast, designed to work with Gaussian and a wide range of non-Gaussian time series, and can locate non-stationarities in time and scale. The test is demo...
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作者：Cook, R. D.; Helland, I. S.; Su, Z.
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Oslo; State University System of Florida; University of Florida
摘要：We build connections between envelopes, a recently proposed context for efficient estimation in multivariate statistics, and multivariate partial least squares (PLS) regression. In particular, we establish an envelope as the nucleus of both univariate and multivariate PLS, which opens the door to pursuing the same goals as PLS but using different envelope estimators. It is argued that a likelihood-based envelope estimator is less sensitive to the number of PLS components that are selected and ...
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作者：Perry, Patrick O.; Wolfe, Patrick J.
作者单位：New York University; University of London; University College London
摘要：Network data often take the form of repeated interactions between senders and receivers tabulated over time. A primary question to ask of such data is which traits and behaviours are predictive of interaction. To answer this question, a model is introduced for treating directed interactions as a multivariate point process: a Cox multiplicative intensity model using covariates that depend on the history of the process. Consistency and asymptotic normality are proved for the resulting partial-li...
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作者：Davis, Richard A.; Klueppelberg, Claudia; Steinkohl, Christina
作者单位：Columbia University; Technical University of Munich
摘要：Max-stable processes have proved to be useful for the statistical modelling of spatial extremes. Several families of max-stable random fields have been proposed in the literature. One such representation is based on a limit of normalized and rescaled pointwise maxima of stationary Gaussian processes that was first introduced by Kabluchko and co-workers. This paper deals with statistical inference for max-stable space-time processes that are defined in an analogous fashion. We describe pairwise...
