Dynamic Data Analysis: Modeling Data with Differential Equations (Springer Series in Statistics)
| Author | : | |
| Rating | : | 4.55 (880 Votes) |
| Asin | : | 1493971883 |
| Format Type | : | paperback |
| Number of Pages | : | 230 Pages |
| Publish Date | : | 2017-05-28 |
| Language | : | English |
DESCRIPTION:
However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. This book fills that gap. . The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis. The
This book fills that gap. . However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into this data analysis landscape. From the Back Cover This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis.&nb