Derivation of Probability Distributions for Risk Assessment Risk assessment is more and more widely applied in different areas. The essence of a risk assessment is to estimate the consequences of adverse events and their probability. For a quantitative judgment of the risks, it is necessary to estimate the uncertainty of the variables that govern the events. The uncertainty is commonly expressed as probability distributions. One of the main problems for the practical application of risk assessments is that the needed probability distributions, usually, are not readily available. These have to be derived from other existing information and knowledge. Several methods have been proposed in the literature for the derivation of probability distr...
In risk assessment of new and existing substances, it is current practice to characterise risk using...
International audienceModels for the assessment of the risk of complex engineering systems are affec...
This paper discusses the challenges involved in the representation and treatment of uncertainties in...
In recent years, we have seen a diverse range of crises and controversies concerning food safety, an...
International audienceExplores methods for the representation and treatment of uncertainty in risk a...
Risk and risk assessment are part of our daily life. Both professionally and privately we make many ...
Uncertainty in situations involving risk is frequently modelled by assuming a plausible form of prob...
Probabilistic risk analysis aims to quantify the risk caused by high technology installations. Incre...
Risk is unavoidable, so quantification of risk in any institution is of great importance as it allow...
Expert judgement is a valuable source of information in risk management. Especially, risk-based deci...
This book is about the formulations, theoretical investigations, and practical applications of new s...
Probability estimates of random events are necessary in many fields of human activity: decision maki...
Difficulties in interpreting probabilities can impede the progress of risk analyses and impair the c...
Markov chain Monte Carlo (MCMC) approaches to sampling directly from the joint posterior distributio...
Quantitative Microbial Risk Assessment Institute HandbookThis chapter provides a review of concepts ...
In risk assessment of new and existing substances, it is current practice to characterise risk using...
International audienceModels for the assessment of the risk of complex engineering systems are affec...
This paper discusses the challenges involved in the representation and treatment of uncertainties in...
In recent years, we have seen a diverse range of crises and controversies concerning food safety, an...
International audienceExplores methods for the representation and treatment of uncertainty in risk a...
Risk and risk assessment are part of our daily life. Both professionally and privately we make many ...
Uncertainty in situations involving risk is frequently modelled by assuming a plausible form of prob...
Probabilistic risk analysis aims to quantify the risk caused by high technology installations. Incre...
Risk is unavoidable, so quantification of risk in any institution is of great importance as it allow...
Expert judgement is a valuable source of information in risk management. Especially, risk-based deci...
This book is about the formulations, theoretical investigations, and practical applications of new s...
Probability estimates of random events are necessary in many fields of human activity: decision maki...
Difficulties in interpreting probabilities can impede the progress of risk analyses and impair the c...
Markov chain Monte Carlo (MCMC) approaches to sampling directly from the joint posterior distributio...
Quantitative Microbial Risk Assessment Institute HandbookThis chapter provides a review of concepts ...
In risk assessment of new and existing substances, it is current practice to characterise risk using...
International audienceModels for the assessment of the risk of complex engineering systems are affec...
This paper discusses the challenges involved in the representation and treatment of uncertainties in...