Add to ORKGnuloWe emphasize the derivation of likelihood models starting from a well specified problem of interest and finite populations. "Parameters" are given operational meaning. In particular, parameters are specified in terms of different forms of energy. Examples relevant to reliability theory are used to illustrate ideas. Examples in engineering probability are given
The decision making (DM) problem is of great practical value in many areas of human activities. Most...
Bayesian methods are common in reliability and risk assessment, however, such methods often demand a...
In this paper, we propose a comprehensive methodology to specify prior distributions for commonly us...
In reliability theory, the most important problem is to determine the reliability of a complex syste...
The development of the theory and application of Monte Carlo Markov Chain methods, vast improvements...
ABSTRACT: In the last decade several authors propagated the use of interval probabilities as alterna...
Successful strategies for maintenance and replacement require good decisions. We might wish to deter...
Successful strategies for maintenance and replacement require good decisions. We might wish to deter...
Successful strategies for maintenance and replacement require good decisions. We might wish to deter...
The objective of this study is to compare Bayesian and parametric approaches to determine the best f...
The objective of this study is to compare Bayesian and parametric approaches to determine the best f...
The exponential distribution is the most widely used reliability analysis. This distribution is very...
The purpose of this project was to investigate the use of Bayesian methods for the estimation of the...
The exponential distribution is the most widely used reliability analysis. This distribution is very...
Especially when facing reliability data with limited information (e.g., a small number of failures),...
The decision making (DM) problem is of great practical value in many areas of human activities. Most...
Bayesian methods are common in reliability and risk assessment, however, such methods often demand a...
In this paper, we propose a comprehensive methodology to specify prior distributions for commonly us...
In reliability theory, the most important problem is to determine the reliability of a complex syste...
The development of the theory and application of Monte Carlo Markov Chain methods, vast improvements...
ABSTRACT: In the last decade several authors propagated the use of interval probabilities as alterna...
Successful strategies for maintenance and replacement require good decisions. We might wish to deter...
Successful strategies for maintenance and replacement require good decisions. We might wish to deter...
Successful strategies for maintenance and replacement require good decisions. We might wish to deter...
The objective of this study is to compare Bayesian and parametric approaches to determine the best f...
The objective of this study is to compare Bayesian and parametric approaches to determine the best f...
The exponential distribution is the most widely used reliability analysis. This distribution is very...
The purpose of this project was to investigate the use of Bayesian methods for the estimation of the...
The exponential distribution is the most widely used reliability analysis. This distribution is very...
Especially when facing reliability data with limited information (e.g., a small number of failures),...
The decision making (DM) problem is of great practical value in many areas of human activities. Most...
Bayesian methods are common in reliability and risk assessment, however, such methods often demand a...
In this paper, we propose a comprehensive methodology to specify prior distributions for commonly us...