Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1150134 | Journal of Statistical Planning and Inference | 2011 | 10 Pages |
Abstract
This paper deals with the problem of estimating the Pearson correlation coefficient when one variable is subject to left or right censoring. In parallel to the classical results on the Pearson correlation coefficient, we derive a workable formula, through tedious computation and intensive simplification, of the asymptotic variances of the maximum likelihood estimators in two cases: (1) known means and variances and (2) unknown means and variances. We illustrate the usefulness of the asymptotic results in experimental designs.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Lei Nie, Yong Chen, Haitao Chu,