Cook's distance was introduced by American statistician R Dennis Cook in
1977. It is used to identify influential data points. It depends on both the
residual and leverage i.e it takes it account both the x value and
y value of the observation.
Steps to compute Cook's distance:
Delete observations one at a time.
Refit the regression model on remaining \(n - 1\) observations
exmine how much all of the fitted values change when the ith observation is deleted.
A data point having a large cook's d indicates that the data point strongly influences the fitted values.