图 书 馆
Copula过程Copula Processes |
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| 课程网址: | http://videolectures.net/nips2010_wilson_cp/ |
| 主讲教师: | Andrew Gordon Wilson |
| 开课单位: | 康奈尔大学 |
| 开课时间: | 2011-03-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We define a copula process which describes the dependencies between arbitrarily many random variables independently of their marginal distributions. As an example, we develop a stochastic volatility model, Gaussian Copula Process Volatility (GCPV), to predict the latent standard deviations of a sequence of random variables. To make predictions we use Bayesian inference, with the Laplace approximation, and with Markov chain Monte Carlo as an alternative. We find our model can outperform GARCH on simulated and financial data. And unlike GARCH, GCPV can easily handle missing data, incorporate covariates other than time, and model a rich class of covariance structures. |
| 关 键 词: | 随机波动率模型; 高斯过程波动率; 贝叶斯推理 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-26：cwx |
| 阅读次数: | 82 |