Premium
Diagnostics for Autocorrelated Regression Models
Author(s) -
Kim SoonKwi,
Huggins Richard
Publication year - 1998
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00007
Subject(s) - autocorrelation , mathematics , autocorrelation technique , statistics , linear regression , curvature , regression analysis , moving average model , regression , linear model , proper linear model , bayesian multivariate linear regression , time series , geometry , autoregressive integrated moving average
This paper discusses the local influence approach to the linear regression model with AR(1) errors. Diagnostics for the autocorrelation models and for the autocorrelation coefficient only are proposed and developed respectively, when simultaneous perturbations of the response vector are allowed. Furthermore, the direction of maximum curvature of local influence analysis is shown to be exactly the same as that in Tsai & Wu (1992) when only the autocorrelation coefficient is of special interest.