Bayesian Methods for Integrated Data Analysis
نویسنده
چکیده
A brief introduction to Bayesian probability theory is given with emphasis on data analysis. The analysis of Thomson scattering data is discussed. Capabilities for assessing diagnostic set-ups are outlined. Extension to more complex analyses aiming at an Integrated Data Analysis of fusion diagnostics are presented. The efforts are motivated both by physics and technical requirements of steady-state fusion devices.
منابع مشابه
Risk Analysis of Operating Room Using the Fuzzy Bayesian Network Model
To enhance Patient’s safety, we need effective methods for risk management. This work aims to propose an integrated approach to risk management for a hospital system. To improve patient’s safety, we should develop flexible methods where different aspects of risk and type of information are taken into consideration. This paper proposes a fuzzy Bayesian network to model and analyze risk in the op...
متن کاملComparison of Bayesian and Frequentist Methods in Estimating the Net Reclassification and Integrated Discrimination Improvement Indices for Evaluation of Prediction Models: Tehran Lipid and Glucose Study
Introduction: The Frequency-based method is commonly used to estimate the Net Reclassification Improvement (NRI)- and Integrated Discrimination Improvement (IDI) indices. These indices measure the magnitude of the performance of statistical models when a new biomarker is added. This method has poor performance in some cases, especially in small samples. In this study, the performance of two Bay...
متن کاملBayesian Melding of Deterministic Models and Kriging for Analysis of Spatially Dependent Data
The link between geographic information systems and decision making approach own the invention and development of spatial data melding method. These methods combine different data sets, to achieve better results. In this paper, the Bayesian melding method for combining the measurements and outputs of deterministic models and kriging are considered. Then the ozone data in Tehran city are analyze...
متن کاملThe Analysis of Bayesian Probit Regression of Binary and Polychotomous Response Data
The goal of this study is to introduce a statistical method regarding the analysis of specific latent data for regression analysis of the discrete data and to build a relation between a probit regression model (related to the discrete response) and normal linear regression model (related to the latent data of continuous response). This method provides precise inferences on binary and multinomia...
متن کاملمقایسه روش بیزی (Bayesian) و کلاسیک در برآرد پارامترهای مدل رگرسیون لجستیک با وجود مقادیر گمشده در متغیرهای کمکی
Background and Aim: Logistic regression is an analytic tool widely used in medical and epidemiologic research. In many studies, we face data sets in which some of the data are not recorded. A simple way to deal with such "missing data" is to simply ignore the subjects with missing observations, and perform the analysis on cases for which complete data are available. Materials and Methods: We c...
متن کاملDeveloping an Integrated Simulation Model of Bayesian-networks to Estimate the Completion Cost of a Project under Risk: Case Study on Phase 13 of South Pars Gas Field Development Projects
Objective: The aim of this paper is to propose a new approach to assess the aggregated impact of risks on the completion cost of a construction project. Such an aggregated impact includes the main impacts of risks as well as the impacts of interactions caused by dependencies among them. Methods: In this study, Monte Carlo simulation and Bayesian Networks methods are combined to present a frame...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003