Ayyub Sheikhy - Department of Statistics, Faculty of mathematics and computer, Shahid Bahonar university of Kerman, Kerman, Iran
Alireza Arabpour - Department of Statistics, Faculty of mathematics and computer, Shahid Bahonar university of Kerman, Kerman, Iran
Mashallah Mashinchi - Department of Statistics, Faculty of mathematics and computer, Shahid Bahonar university of Kerman, Kerman, Iran
R. Pourmousa - Department of Statistics, Faculty of mathematics and computer, Shahid Bahonar university of Kerman, Kerman, Iran
Mohsen Rezapour - Department of Statistics, Faculty of mathematics and computer, Shahid Bahonar university of Kerman, Kerman, Iran
Mohammad Javad Roastami - Department of Computer Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Khosravi Mohsen - Department of Statistics, Faculty of mathematics and computer, Shahid Bahonar university of Kerman, Kerman, Iran
Amin Abbdollah Nejad - Kerman Chamber of Commerce, Industries, Mines and Agriculture, Kerman, Iran
Abed Badakhshan - Department of Statistics, Faculty of mathematics and computer, Shahid Bahonar university of Kerman, Kerman, Iran

In this work we carry out a multiple imputation technique for handling missing observations. We propose an algorithm, which performs a hierarchical multiple imputation using edition rules to impute missing values. We assess our algorithm using a simulation study and a numerical application of our algorithm in dataset of Kerman Chamber of Commerce, Industries, Mines and Agriculture is presented for more illustration.

Missing Data, Multiple Imputation, Editing Rules, Data Cleaning