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SUMMARY: Multivariate versions of variable bandwidth kernel density estimators can be used to combat the eeects of the curse of dimensionality. They are also more exible than the xed bandwidth estimator to model complex (multimodal) densities. In this work, two variable bandwidth estimators are discussed: the balloon estimator which varies the smoothing(More)
Modern data analysis requires a number of tools to undercover hidden structure. For initial exploration of data, animated scatter diagrams and nonparametric density estimation in many forms and varieties are the techniques of choice. This article focuses on the application of histograms and nonparametric kernel methods to explore data. The details of(More)
In this paper, theoretical and practical aspects of the sample-point adaptive positive kernel density estimator are examined. A closed-form expression for the mean integrated squared error is obtained through the device of preprocessing the data by binning. With this expression, the exact behavior of the optimally adaptive smoothing parameter function is(More)
[1] We present probabilistic projections for spatial patterns of future temperature change using a multivariate Bayesian analysis. The methodology is applied to the output from 21 global coupled climate models used for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The statistical technique is based on the assumption that(More)
The need for improvements over the xed kernel density estimator in certain situations has been discussed extensively in the literature, particularly in the application of density estimation to mode hunting. Problem densities often exhibit skewness or multimodality with diierences in scale for each mode. By varying the bandwidth in some fashion, it is(More)
OBJECTIVE Cerebral cavernous malformations (CCMs) are focal dysmorphic blood vessel anomalies predisposing individuals to hemorrhagic stroke and epilepsy. CCMs are sporadic or inherited as autosomal dominant disease with three known genes. The hypothesis that genetic heterogeneity would account for the remarkable variability in CCM manifestations was(More)
Functional analysis of variance (ANOVA) models partition a functional response according to the main effects and interactions of various factors. This article develops a general framework for functional ANOVA modeling from a Bayesian viewpoint, assigning Gaussian process prior distributions to each batch of functional effects. We discuss the choices to be(More)