Distributed-lag Linear Structural Equation Models in R: The d1sem Package

被引：0

作者：

Magrini, Alessandro ^{[1
]}

机构：

[1] Univ Florence, Dept Stat Comp Sci Applicat, Florence, Italy

来源：

AUSTRIAN JOURNAL OF STATISTICS | 2019年 / 48卷 / 02期

关键词：

constrained lag shapes; directed acyclic graphs; dynamic causal inference; probabilistic graphical models; time series; LIKELIHOOD;

D O I：

10.17713/ajs.v48i2.777

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：

In this paper, an extension of linear Markovian structural causal models is introduced, called distributed-lag linear structural equation models (DLSEMs), where each factor of the joint probability distribution is a distributed-lag linear regression with constrained lag shapes. DLSEMs account for temporal delays in the dependence relationships among the variables and allow to assess dynamic causal effects. As such, they represent a suitable methodology to investigate the effect of an external impulse on a multidimensional system through time. In this paper, we present the dlsem package for R implementing inference functionalities for DLSEMs. The use of the package is illustrated through an example on simulated data and a real-world application aiming at assessing the impact of agricultural research expenditure on multiple dimensions in Europe.

引用

页码：14 / 42

页数：29