A unified approach on residuals, leverages and outliers in the linear mixed model

Autor:	Temesgen Zewotir, J.S. Galpin
Rok vydání:	2007
Předmět:	Statistics and Probability Mixed model Proper linear model Best linear unbiased prediction computer.software_genre Residual Generalized linear mixed model Outlier Linear regression Statistics Leverage (statistics) Data mining Statistics Probability and Uncertainty computer Mathematics
Zdroj:	TEST. 16:58-75
ISSN:	1863-8260 1133-0686
DOI:	10.1007/s11749-006-0001-2
Popis:	Although the linear mixed model can be viewed as a direct extension of multiple regression, it is not obvious how to generalize the standard diagnostic tools such as residual analysis and detection of leverage points and outliers, which are available in the linear regression situation. A unified approach to residuals, leverages and outliers in the linear mixed model is developed. Formal and informal procedures are proposed to display the general features of residuals and leverages in order to detect outliers and high-leverage points in the linear mixed models. The relationship between the best linear unbiased predictor (BLUP) and residuals is established. Some properties of BLUPs are formulated and their use in detecting outlying observations are investigated.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ec8472669f1a1c8ffee5fb5f7ced26c0 https://doi.org/10.1007/s11749-006-0001-2 Zobrazit plný text záznamu Full text from SpringerLink