Now showing items 1-3 of 3
Filling missing data using interpolation methods: Study on the effect of fitting distribution
(Trans Tech Publications, 2014)
The presence of missing values in statistical survey data is an important issue to deal with. These data usually contained missing values due to many factors such as machine failures, changes in the siting monitors, routine ...
Estimation of missing values in air pollution data using single imputation techniques
(Science Society of Thailand, 2008)
Air pollution data obtained using automated machines often contain missing values which can cause bias due to systematic differences between observed and unobserved data. We used interpolation and mean imputation techniques ...
Comparison of Linear Interpolation Method and Mean Method to Replace the Missing Values in Environmental Data Set
(Universiti Malaysia Perlis (UniMAP), 2007-06-09)
Missing data is a very frequent problem in many scientific field including environmental research. These are usually due to machine failure, routine maintenance, changes in siting monitors and human error. Incomplete ...