| 期刊全称 | Advanced Data Analysis in Neuroscience | | 期刊简称 | Integrating Statisti | | 影响因子2023 | Daniel Durstewitz | | 视频video | | | 发行地址 | Designed for use as a textbook in statistics for students from the neuro- and biosciences.Integrates statistical analysis with a dynamical systems perspective and computational modeling.Reviews almost | | 学科分类 | Bernstein Series in Computational Neuroscience | | 图书封面 |  | | 影响因子 | .This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most method | | Pindex | Textbook 2017 |
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发表于 2025-3-21 16:55:27
