On Identifying Influential Observations in the Presence of Multicollinearity ()
ABSTRACT
Influential observation is one which either individually or together with
several other observations has a demonstrably large impact on the values of
various estimates of regression coefficient. It has been suggested by some
authors that multicollinearity should be controlled before attempting to
measure influence of data point. In using ridge regression to mitigate the
effect of multicollinearity, there arises a problem of choosing possible of
ridge parameter that guarantees stable regression coefficients in the
regression model. This paper seeks to check whether the choice of ridge
parameter estimator influences the identified influential data points.
Share and Cite:
Uzuke, C. and Ezeilo, I. (2021) On Identifying Influential Observations in the Presence of Multicollinearity.
Open Journal of Statistics,
11, 290-302. doi:
10.4236/ojs.2021.112016.
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