.png){kind=icon}
返回
Linearity testing for fuzzy rule-based models
.png){kind=icon}
PRE
AI
DOI：10.1016/j.fss.2010.01.005.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we introduce a linearity test for fuzzy rule-based models in the framework of time series modeling. To do so, we explore a family of statistical models, the regime switching autoregressive models, and the relations that link them to the fuzzy rule-based models. From these relations, we derive a Lagrange multiplier linearity test and some properties of the maximum likelihood estimator needed for it. Finally, an empirical study of the goodness of the test is presented. (C) 2010 Elsevier B.V. All rights reserved.
Keyword:
Fuzzy rule-based models
Time series
Linearity test
Statistical inference
期刊
IF:
2.7
论文数:
7.6K
被引数:
1.5W
机构
引用论文
.png){kind=icon}
Smooth transition autoregressive models and fuzzy rule-based systems: Functional equivalence and consequences平滑过渡自回归模型和基于模糊规则的系统: 功能等价和后果
PREAI
分享收藏
查看更多内容