Distribution fitting for incomplete data
This report reviews the effects of missing data on probability distributions which covers two main topics: (1) types of probability distributions and goodness-of-fit tests, and (2) missing data mechanisms and missing data techniques (MDT). The focus is to investigate the effects of missing d...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
2011
|
| 主題: | |
| 在線閱讀: | http://hdl.handle.net/10356/45865 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | This report reviews the effects of missing data on probability distributions which covers two main topics: (1) types of probability distributions and goodness-of-fit tests, and (2) missing data mechanisms and missing data techniques (MDT).
The focus is to investigate the effects of missing data of a specified probability distribution and determine the best methods to fill in the missing values. An overview and comparison of the complete-data cases and incomplete-data cases are provided. Multiple imputation and Listwise Deletion, which are the two MDTs used are also discussed. |
|---|