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

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

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

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...

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...

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

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

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...

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

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

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...

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

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

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 ...

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 ...

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...

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

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...

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

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