Browsing by Subject "Missing values"

Now showing items 1-8 of 8

    • Comparison of Linear Interpolation Method and Mean Method to Replace the Missing Values in Environmental Data Set 

      Norazian, Mohamed Noor; Mohd Mustafa, Al Bakri Abdullah; Ahmad Shukri, Yahaya; Nor Azam, Ramli (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 ...

    • Estimating missing data in air pollution data using interpolation technique: effects on fitting Gamma Distribution 

      Norazian, Mohamed Noor; Mohd Mustafa, Al Bakri Abdullah; Ahmad Shukri, Yahaya; Nor Azam, Ramli (Universiti Sains Malaysia (USM) & Malaysian Mathematical Sciences Society, 2007-12-06)
      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 for air pollution data using Interpolation technique 

      Norazian, Mohamed Noor; Mohd Mustafa, Al Bakri Abdullah; Ahmad Shukri, Yahaya; Nor Azam, Ramli (Universiti Malaysia Perlis, 2006)
      Air pollution data such as PM10, sulphur dioxide, ozone and carbon monoxide are usually obtained using automated machines located at different sites. These are usually due to mechanical failure, routine maintenance, changes ...

    • Estimation of missing values in air pollution data using single imputation techniques 

      Norazian, Mohamed Noor; Shukri, Yahaya Ahmad; Azam, Ramli Nor; Mohd. Mustafa Al Bakri, Abdullah (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 ...

    • Filling missing data using interpolation methods: Study on the effect of fitting distribution 

      Norazian, Mohamed Noor; Ahmad Shukri, Yahaya, Prof. Madya; Nor Azam, Ramli, Prof. Dr.; Mohd Mustafa Al Bakri, Abdullah (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 ...

    • Missing values imputation for wind speed 

      Nur Arina Bazilah, Kamisan; Siti Mariam Norrulashikin; Siti Fatimah, Hassan (Institute of Engineering Mathematics, Universiti Malaysia Perlis, 2021-12)
      Addressing missing values is important in the process of getting a precise and accurate result. If missing data are not treated appropriately, then the results could lead to biased estimates. But different series may require ...

    • The Replacement of Missing Values of Continous Air Pollution Monitoring Data using Mean Top Bottom Imputation technique 

      Norazian, Mohamed Noor; Ahmad Shukri, Yahaya; Nor Azam, Ramli; Mohd Mustafa, Al Bakri Abdullah (Kolej Universiti Kejuruteraan Utara Malaysia, 2006)
      Air pollutants data such as PM10 carbon monoxide, sulphur dioxide and ozone concentration were obtained from automated monitoring stations. These data usually contain missing values that can cause bias due to systematic ...

    • SSDEM: Statistical Software for Fitting Distribution and Estimating Missing Values in Environmental Data Sets 

      Norazian, Mohamed Noor; Ahmad Shukri, Yahaya, Prof. Madya; Mohd Mustafa, Al Bakri Abdullah; Abdul Haqi, Ibrahim; Mohd Lufti, Zainudin (School of Environmental Engineering, 2008-01-09)
      The first software that focused on estimating missing values. Uses the best mathematical equation to estimate the missing data (based on literature). Simple applications assist the user shorten the time needed for estimating ...