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Modern scientific technology is providing a new class of simultaneous inference problems for the applied statistician, where there are hundreds or thousands or even more hypothesis tests to co...
Empirical Bayes methods use the data from parallel experiments, for instance observtions Xk  N (k;1) for k = 1;2; : : : ; N, to estimate the conditional distributions kjXk. There are two main estima...
Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consider bootstrap methods for computing standard errors and con dence intervals that take model selecti...
Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consider bootstrap methods for computing standard errors and con dence intervals that take model selecti...
I started looking at log-concave distributions when I was searching for an appropriate model for subpopulations of multivariate flow cytometry data about ten years ago. The use of log-concave ...
In this study, we demonstrate the use of a geo-spatial information system for volume estimation of fallout deposits and for identification of syn-eruptive and post-eruptive depositional mechanisms. Fo...
In this paper, we use calibrated images collected by the video-surveillance system of the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, to retrieve the height of the eruption col...
Fundamental tasks in computer vision include determining the position, orientation and trajectory of a moving camera relative to an observed object or scene. Many such visual tracking algorithms hav...
In this paper the South African Ionospheric Map (SAIM) is upgraded with the usage of recent International Reference Ionosphere (IRI)-2012 model and South African Bottomside Model (SABIM) version 5 and...
We evaluate the potential of deriving a vegetation leaf area index (LAI) from small footprint airborne laser scanning data. Based on findings from large area histograms of discrete laser return...
The present study focuses on the unexplored area of application of artificial neural network in groundwater hydrology. Three models, each based on artificial neural networks, are applied for predictio...
The most important practical and critical problem related to the performance of reservoirs is the estimation of storage capacity loss due to sedimentation process. The problem to be addressed is to es...
Annual extreme rainfall series of 1-3 day durations at stations located inside the Indus basin in India were subjected to statistical analysis in order to estimate point Probable Maximum Precipitation...
A method is presented for parameter set estimation of open-loop stable systems with uncertain parameters and quasi-stationary disturbances. The system model is assumed to contain both parametric and n...
Policies for the joint identification and control of uncertain systems are presented. The discussion focuses on the case of a multiple input, single output linear system, with no dynamics and quadrati...

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