Introduction. In this study, we aimed to demonstrate the correlation of FGF-23 levels with bone-mineral metabolism, anemia, and the treatment in dialysis patients. Methods. Eighty-nine patients with similar age, gender, dialysis duration, and dialysis adequacy who were receiving hemodialysis replacement therapy for at least 6 months were included in the study. Serum iron, iron binding capacity,...

BACKGROUND In 2008, Australian Family Physician (AFP) was accepted on the list of journals listed in Science Citation Index Expanded and, thus, will generate an impact factor over the next 2 years. Impact factor is important to authors from research and academic backgrounds and will make AFP an increasingly attractive journal in which to publish. AIM To describe the impact factor, its method ...

This chapter is dedicated to scope of the application of Importance Sampling Techniques to the design phase of Neyman-Pearson Neural Detectors. This phase usually requires the application of MonteCarlo trials in order to estimate some performance parameters. The classical Monte-Carlo method is suitable to estimate high event probabilities but not suitable to estimate very low event probabilitie...

The process to certify highly Automated Vehicles has not yet been defined by any country in the world. Currently, companies test Automated Vehicles on public roads, which is time-consuming and inefficient. We proposed the Accelerated Evaluation concept, which uses a modified statistics of the surrounding vehicles and the Importance Sampling theory to reduce the evaluation time by several orders...

Evaluating a policy by deploying it in the real world can be risky and costly. Off-policy evaluation (OPE) algorithms use historical data collected from running a previous policy to evaluate a new policy, which provides a means for evaluating a policy without requiring it to ever be deployed. Importance sampling is a popular OPE method because it is robust to partial observability and works wit...

The paper introduces AND/OR importance sampling for probabilistic graphical models. In contrast to importance sampling, AND/OR importance sampling caches samples in the AND/OR space and then extracts a new sample mean from the stored samples. We prove that AND/OR importance sampling may have lower variance than importance sampling; thereby providing a theoretical justification for preferring it...

This paper describes a discrete-time retrial queue and shows how importance sampling simulations can be applied for estimating the probability of large orbit content and the overflow fraction of primary calls.

We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the number and locations of the kernels. Our algorithm overcomes some of the computational difficulties related to batch methods for kernel regression. It is non-iterative, and requires only a single pass over the data. It is ...