Methodology and Computing in Applied Probability
Methodology and Computing in Applied Probability publishes high quality research and review articles in areas of applied probability that emphasize methodology and computing. The journal focuses on articles that examine important applications and that include detailed case studies.
With its policy of attracting papers representing a broad range of interests, the journal covers such topics as algorithms, approximations, combinatorial and geometric probability, communication networks, extreme value theory, finance, image analysis, inequalities, information theory, mathematical physics, molecular biology, Monte Carlo methods, order statistics, queuing theory, reliability theory, and stochastic processes.
An Algorithm for Prior Elicitation in Dynamic Bayesian Models for Proportions with the Logit Link Function
- Journal Title
- Methodology and Computing in Applied Probability
- Volume 1 / 1999 - Volume 20 / 2018
- Print ISSN
- Online ISSN
- Springer US
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