Open Access. Powered by Scholars. Published by Universities.®
Other Statistics and Probability Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Bayesian Model Averaging and Semiparametric Regression (2)
- Copula Modeling (2)
- Analysis (1)
- Archimedian Copula (1)
- Asymmetric Dependence (1)
-
- Bayesian Cross-Validation (1)
- Bayesian Pair-Copula Selection (1)
- Computing (1)
- Discrete Longitudinal Data (1)
- Distribution (1)
- Education (1)
- Electricity Market Efficiency (1)
- Electricity Spot Prices (1)
- Markov chain Monte Carlo (1)
- Multivariate Dependence (1)
- Multivariate Discrete Data (1)
- Multivariate Models in Marketing (1)
- Nonlinear Dependence (1)
- Online Advertising (1)
- Simulation (1)
- Statistics (1)
- Vine Copulas. (1)
- Website Exposure (1)
- Publication
- Publication Type
Articles 1 - 3 of 3
Full-Text Articles in Other Statistics and Probability
Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison
Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison
Statistics
As a student, I noticed that the statistical package R (http://www.r-project.org) would have several benefits of its usage in the classroom. One benefit to the package is its free and open-source nature. This would be a great benefit for instructors and students alike since it would be of no cost to use, unlike other statistical packages. Due to this, students could continue using the program after their statistical courses and into their professional careers. It would be good to expose students while they are in school to a tool that professionals use in industry. R also has powerful …
Modeling Dependence Using Skew T Copulas: Bayesian Inference And Applications, Michael S. Smith, Quan Gan, Robert Kohn
Modeling Dependence Using Skew T Copulas: Bayesian Inference And Applications, Michael S. Smith, Quan Gan, Robert Kohn
Michael Stanley Smith
[THIS IS AN AUGUST 2010 REVISION THAT REPLACES ALL PREVIOUS VERSIONS.]
We construct a copula from the skew t distribution of Sahu, Dey & Branco (2003). This copula can capture asymmetric and extreme dependence between variables, and is one of the few copulas that can do so and still be used in high dimensions effectively. However, it is difficult to estimate the copula model by maximum likelihood when the multivariate dimension is high, or when some or all of the marginal distributions are discrete-valued, or when the parameters in the marginal distributions and copula are estimated jointly. We therefore propose …
Estimation Of Copula Models With Discrete Margins Via Bayesian Data Augmentation, Michael S. Smith, Mohamad A. Khaled
Estimation Of Copula Models With Discrete Margins Via Bayesian Data Augmentation, Michael S. Smith, Mohamad A. Khaled
Michael Stanley Smith
Estimation of copula models with discrete margins is known to be difficult beyond the bivariate case. We show how this can be achieved by augmenting the likelihood with latent variables, and computing inference using the resulting augmented posterior. To evaluate this we propose two efficient Markov chain Monte Carlo sampling schemes. One generates the latent variables as a block using a Metropolis-Hasting step with a proposal that is close to its target distribution, the other generates them one at a time. Our method applies to all parametric copulas where the conditional copula functions can be evaluated, not just elliptical copulas …