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Veröffentlicht/Copyright:
1. März 2020
Published Online: 2020-03-01
Published in Print: 2020-03-01
© 2020 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Why simple quadrature is just as good as Monte Carlo
- Describing the Pearson 𝑅 distribution of aggregate data
- Approximation of Euler–Maruyama for one-dimensional stochastic differential equations involving the maximum process
- A Bayesian inference for the penalized spline joint models of longitudinal and time-to-event data: A prior sensitivity analysis
- A Bayesian procedure for bandwidth selection in circular kernel density estimation
Artikel in diesem Heft
- Frontmatter
- Why simple quadrature is just as good as Monte Carlo
- Describing the Pearson 𝑅 distribution of aggregate data
- Approximation of Euler–Maruyama for one-dimensional stochastic differential equations involving the maximum process
- A Bayesian inference for the penalized spline joint models of longitudinal and time-to-event data: A prior sensitivity analysis
- A Bayesian procedure for bandwidth selection in circular kernel density estimation
