Contents：
主講人：李宗翰博士(陽明交通大學的統計學研究所博士後研究員)
Abstract:
Confidence intervals for the mean of discrete exponential families are widely used in many applications. Since missing data are commonly encountered, the interval estimation for incomplete data is an important problem. The performances of the existing multiple imputation confidence intervals are unsatisfactory. We propose modified multiple imputation confidence intervals to improve the existing confidence intervals for the mean of the discrete exponential families with quadratic variance functions. The simulation study shows that the coverage probabilities of the modified confidence intervals are closer to the nominal level compared with the existing confidence intervals. These confidence intervals are also illustrated with a real data example.
Category：Faculty training in teaching
Time：
2021/06/08 14:10 ~ 2021/06/08 16:00
Registration period：
2021/05/13 15:00 ~ 2021/06/08 12:00
Location：
科學館 S433室
Duration：2.0 hours
Registration Limit：30 (Current Registrants：9）
Attendees：teachers、students、staff