Statistical Challenges in Agent-Based Modeling

被引:8
|
作者
Banks, David L. [1 ]
Hooten, Mevin B. [2 ]
机构
[1] Duke Univ, Dept Stat Sci, Durham, NC 27708 USA
[2] US Geol Survey, Dept Fish Wildlife & Conservat Biol, Colorado Cooperat Fish & Wildlife Res Unit, Ft Collins, CO USA
来源
AMERICAN STATISTICIAN | 2021年 / 75卷 / 03期
关键词
Emulator; Individual-based model; Mechanistic model;
D O I
10.1080/00031305.2021.1900914
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Agent-based models (ABMs) are popular in many research communities, but few statisticians have contributed to their theoretical development. They are models like any other models we study, but in general, we are still learning how to fit ABMs to data and how to make quantified statements of uncertainty about the outputs of an ABM. ABM validation is also an underdeveloped area that is ripe for new statistical developments. In what follows, we lay out the research space and encourage statisticians to address the many research issues in the ABM ambit.
引用
收藏
页码:235 / 242
页数:8
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