Evaluating Data Editing and Imputation Methods based on Monte Carlo Technique
碩士 === 國防大學管理學院 === 財務管理學系 === 99 === Most of the survey will have missing data, if the database contains missing values would seriously affect the quality of data analysis, how to properly handle missing values is an important issue. Although a number of imputation methods have been proposed, but n...
Main Authors: | Cheng, Chengyen, 鄭丞晏 |
---|---|
Other Authors: | Tsai, Hsiangjung |
Format: | Others |
Language: | zh-TW |
Published: |
2011
|
Online Access: | http://ndltd.ncl.edu.tw/handle/66349977077326286387 |
Similar Items
-
Random Number Generation and Monte Carlo Methods (2nd edition)
by: Rodney Sparapani
Published: (2004-09-01) -
Data Editing and Imputation in Business Surveys Using “R”
by: Elena Romascanu
Published: (2014-06-01) -
Flexible Imputation of Missing Data (2nd Edition)
by: Abdolvahab Khademi
Published: (2020-04-01) -
On the analysis of Monte Carlo and quasi-Monte Carlo methods
by: Dickinson, Andrew Samuel
Published: (2004) -
Evaluation of Measurement Uncertainty Based on Monte Carlo Method
by: Wang X M, et al.
Published: (2018-01-01)