Probabilistic Forecasting and Bayesian Data Assimilation

栀子花开

Probabilistic Forecasting and Bayesian Data Assimilation

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. Probabilistic Forecasting and Bayesian Data Assimilation.pdf (8.78 MB, 下载次数: 1, 售价: 3 金钱)

2016-12-20 15:39 上传

点击文件名下载附件

秀才遇上兵

越简单越霸气

感谢楼主分享