Brenda MacGibbon

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A data set on categories of congenital heart malformations for sibling pairs (with different malformations) of Fraser and Hunter (1975) is analyzed exactly ...

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The spatially inhomogeneous smoothness of nonparametric methods is often modelled by Besov and Triebel-type smoothness constraints. For such problems, Donoh...

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Inspired by previous results on asymptotic minimax estimation for a ball of increasing radius in R<sup><i>n</i></sup>, we study the analogous problem for do...

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The goal in many data analyses is to produce brief summaries which convey the key conclusions. This will be particularly important in survival analysis in m...

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Since Hinkley's original work on exact inference for a change in a sequence of random variables, many authors have proposed different methods based either o...

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The search for optimal non-parametric estimates of the cumulative distribution and hazard functions under order constraints inspired at least two earlier cl...

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One important challenge in nonparametric density and regression-function estimation is spatially inhomogeneous smoothness. This is often modelled by Besov-t...

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We present a method for the integral representation of local and global diffeomorphisms between subsets of <img src="G9942-1.gif" align=bottom> and <img src...

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The spatially inhomogeneous smoothness of the non-parametric density or regression-function to be estimated by non-parametric methods is often modelled by B...

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Non-parametric estimation of smooth functions belonging to Sobolev classes is closely related to the problem of estimating the (infinite dimensional) mean o...

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The minimax global asymptotic rate of convergence for the estimation of a hazard function in the presence of random right censoring is obtained using the li...

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In the modeling of biological phenomena, in living organisms whether the measurements are of blood pressure, enzyme levels, biomechanical movements or heart...

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Here we propose a general class of generalized linear models to describe time series of counts <i>Y</i><sub>1</sub>, ... ,<i>Y<sub>n</sub></i>. Following Ze...

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One of the main advantages of the discrete wavelet representation is the near-optimal estimation of signals corrupted with noise. After the seminal work of ...

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In this paper we derive a law of the logarithm establishing the exact rate of uniform convergence for nearest neighbor kernel estimators of the density and ...

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In many medical experiments data are collected across time, over a number of similar trials or a number of experimental units. As is the case of neural spik...

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The utility of Bayes and empirical Bayes techniques is illustrated on an important problem often encountered in small area estimation. We propose various Ba...

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Estimation of the mean of a multivariate normal distribution is considered. The components of the mean vector are assumed to be intra-block exchangeable; t...

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The use of nonparametric regression techniques for binary regression is a promising alternative to parametric methods. As in other nonparametric smoothing ...

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There has been much recent statistical research in the area of inference under constraints. Here we consider the problem of bounded parameter estimation, in...

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