scholarly journals Bayesian estimation and modeling: Editorial to the second special issue on Bayesian data analysis.

2017 ◽  
Vol 22 (4) ◽  
pp. 609-615 ◽  
Author(s):  
Sy-Miin Chow ◽  
Herbert Hoijtink
Keyword(s):  
Data Analysis ◽  
Bayesian Estimation ◽  
Special Issue ◽  
Bayesian Data Analysis

Estimation of Failure Probability and its Applications in Reliability Data Analysis

2010 ◽  
Vol 118-120 ◽  
pp. 601-605
Author(s):  
Han Ming
Keyword(s):  
Parameter Estimation ◽  
Data Analysis ◽  
Bayesian Estimation ◽  
Failure Probability ◽  
Evaluation Method ◽  
Estimation Method ◽  
New Method ◽  
Reliability Parameter ◽  
Hierarchical Bayesian Estimation ◽  
Definition Of

Evaluation method of reliability parameter estimation needs to be improved effectively with the advance of science and technology. This paper develops a new method of parameter estimation, which is named E-Bayesian estimation method. In the case one hyper-parameter, the definition of E-Bayesian estimation of the failure probability is provided, moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation, and the property of E-Bayesian estimation of the failure probability are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.

2nd Special issue on Functional Data Analysis

2021 ◽  
Author(s):  
Frederic Ferraty ◽  
Alois Kneip ◽  
Piotr Kokoszka ◽  
Alex Petersen
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Special Issue

A Bayesian Data Analysis System for the Evaluation of Social Programs

1977 ◽  
Vol 72 (360) ◽  
pp. 711 ◽  
Author(s):  
Ming-Mei Wang ◽  
Melvin R. Novick ◽  
Gerald L. Isaacs ◽  
Dan Ozenne
Keyword(s):  
Data Analysis ◽  
Social Programs ◽  
Bayesian Data Analysis ◽  
Analysis System ◽  
Data Analysis System

scholarly journals Bayesian data analysis in the phonetic sciences: A tutorial introduction

2018 ◽  
Vol 71 ◽  
pp. 147-161 ◽  
Author(s):  
Shravan Vasishth ◽  
Bruno Nicenboim ◽  
Mary E. Beckman ◽  
Fangfang Li ◽  
Eun Jong Kong
Keyword(s):  
Data Analysis ◽  
Bayesian Data Analysis

Mathematics and Statistics in Anesthesiology

2018 ◽  
Author(s):  
Daniel Mortlock
Keyword(s):  
Probability Theory ◽  
Data Analysis ◽  
Survey Design ◽  
Probability Distributions ◽  
Statistical Tests ◽  
Real World Data ◽  
Mathematical Functions ◽  
P Values ◽  
Bayesian Data Analysis ◽  
Probability And Statistics

Mathematics is the language of quantitative science, and probability and statistics are the extension of classical logic to real world data analysis and experimental design. The basics of mathematical functions and probability theory are summarized here, providing the tools for statistical modeling and assessment of experimental results. There is a focus on the Bayesian approach to such problems (ie, Bayesian data analysis); therefore, the basic laws of probability are stated, along with several standard probability distributions (eg, binomial, Poisson, Gaussian). A number of standard classical tests (eg, p values, the t-test) are also defined and, to the degree possible, linked to the underlying principles of probability theory. This review contains 5 figures, 1 table, and 15 references. Keywords: Bayesian data analysis, mathematical models, power analysis, probability, p values, statistical tests, statistics, survey design

scholarly journals Special Issue Editorial: Intelligent Data Analysis for Sustainable Computing

2020 ◽  
Vol 5 (3) ◽  
pp. 304-307
Author(s):  
Yulei Wu ◽  
Yi Pan ◽  
Nektarios Georgalas ◽  
Geyong Min
Keyword(s):  
Data Analysis ◽  
Intelligent Data Analysis ◽  
Special Issue
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