A class of bootstrap based residuals for compositional data
arxiv(2024)
摘要
Regression models for compositional data are common in several areas of
knowledge. As in other classes of regression models, it is desirable to perform
diagnostic analysis in these models using residuals that are approximately
standard normally distributed. However, for regression models for compositional
data, there has not been any multivariate residual that meets this requirement.
In this work, we introduce a class of asymptotically standard normally
distributed residuals for compositional data based on bootstrap. Monte Carlo
simulation studies indicate that the distributions of the residuals of this
class are well approximated by the standard normal distribution in small
samples. An application to simulated data also suggests that one of the
residuals of the proposed class is better to identify model misspecification
than its competitors. Finally, the usefulness of the best residual of the
proposed class is illustrated through an application on sleep stages. The class
of residuals proposed here can also be used in other classes of multivariate
regression models.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要