This paper is concerned with the influence of incomplete data due to random missing values in the multiple linear regression problem. Using the idea of Hampel's influence function, a partial influence function is derived and shown to be useful in several indications. Comparisons with the complete data situation and with the empirical case-deletion distance measure are also given.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- EM algorithm
- influence function
- missing values
- multiple linear regression