& Conclusions-Risk analysis is discussed within a Bayes framework. Traditionally, Bayes parameter estimation is based on a quadratic loss-function. This paper introduces an alternative asymmetric precautionary loss-function, derives its main features, and presents a general class of precautionary loss-functions with the quadratic loss-function as a special case. These loss functions approach in...

Microwave remote sensing provides an excellent means for mapping polar sea ice extent. In this study, a new algorithm for polar sea ice mapping is developed for use with the SeaWinds instrument. The approach utilizes a priori information within the framework of Bayes detection to produce sea ice extent maps. Statistical models for sea ice and ocean are represented in histograms which are filter...

This report constitutes an unrefereed manuscript which is intended to be submitted for publication. Any opinions and conclusions expressed in this report are those of the author(s) and do not necessarily represent the views of the Institute. This paper deals with Bayesian models given by statistical experiments and common types of loss functions. Probability of error of the Bayes identificator ...

Studying small effects or subtle neuroanatomical variation requires large-scale sample size data. As a result, combining neuroimaging data from multiple datasets is necessary. Variation in acquisition protocols, magnetic field strength, scanner build, and many other non-biologically related factors can introduce undesirable bias into studies. Hence, harmonization required to remove the bias-ind...

In this paper, we propse Bayes estimators of the parameters of Marshall Olkin extended exponential distribution (MOEED) introduced by Marshall-Olkin [2] for complete sample under squared error loss function (SELF). We have used different approximation techniques to obtain the Bayes estimate of the parameters. A Monte Carlo simulation study is carried out to compare the performance of proposed e...

In this paper, we construct a point estimator when assuming unequal and unknown variances by using the empirical Bayes approach in the classical normal mean problem. The proposed estimator shrinks both means and variances, and is thus called the double shrinkage estimator. Extensive numerical studies indicate that the double shrinkage estimator has lower Bayes risk than the estimator which shri...

Large Vocabulary Continuous Speech Recognition (LVCSR) systems often use a multi-pass recognition framework where the final output is obtained from a combination of multiple models. Previous systems within this framework have normally built a number of independently trained models, before performing multiple experiments to determine the optimal combination. For two models to give improvements u...

The aim of this study was to establish a computer-aided estimating system for determining the risk of development of gastric cancer, achieved by image processing on an ordinary endoscopic picture. Digital endoscopic pictures of the background gastric mucosa in 26 Helicobacter pylori (H. pylori) positive patients with early intestinal type gastric cancer and age-gendermatched H. pylori positive ...