Imputing missing values in modelling the PM10 concentrations

QR Code

Imputing missing values in modelling the PM10 concentrations

Missing values have always been a problem in analysis. Most exclude the missing values from the analyses which may lead to biased parameter estimates. Some imputations methods are considered in this paper in which simulation study is conducted to compare three methods of imputation namely mean subst...

Full description

Bibliographic Details
Main Authors:	Nuradhiathy Abd Razak, Yong Zulina Zubairi, Rossita M. Yunus
Format:	Article
Language:	English
Published:	Universiti Kebangsaan Malaysia 2014
Online Access:	http://journalarticle.ukm.my/7824/ http://journalarticle.ukm.my/7824/1/18_Nuradhiathy.pdf

Similar Items

Imputation techniques for incomplete load data based on seasonality and orientation of the missing values
by: Nur Arina Bazilah Kamisan,, et al.
Published: (2020)

Imputation methods on daily PM10 data (2010-15)
by: Abd Rani, Nurul Latiffah, et al.
Published: (2019)

An Evaluation of Machine Learning Algorithms for Missing Values Imputation
by: Kohbalan, Moorthy, et al.
Published: (2019)

Missing values imputation tool using imputex algorithm
by: Sidi, Fatimah, et al.
Published: (2024)

Survival modelling, missing values and frailty with application to cervical cancer data / Nuradhiathy Abd Razak
by: Nuradhiathy, Abd Razak
Published: (2016)

Artificial neural network forecasting performance with missing value imputations
by: Abd Rahman, Nur Haizum, et al.
Published: (2020)

Performance analysis of machine learning algorithms for missing value imputation
by: Zainal Abidin, Nadzurah, et al.
Published: (2018)

Systematic review of using machine learning in imputing missing values
by: Alabadla, Mustafa, et al.
Published: (2022)

Missing-values imputation algorithms for microarray gene expression data
by: Moorthy, Kohbalan, et al.
Published: (2019)

Systematic review of using machine learning in imputing missing values
by: Alabadla, Mustafa, et al.
Published: (2022)

Filling the gaps: Imputation of missing metrics’ values in a software quality model
by: Kupinski, S., et al.
Published: (2017)

Interval estimation of the concentration parameter and missing value imputation in the von mises distribution / Nor Hafizah Moslim
by: Nor Hafizah , Moslim
Published: (2022)

Evaluation of missing values imputation methods towards the effectiveness of asset valuation prediction model
by: Mohd Jaya, Mohd Izham, et al.
Published: (2019)

ExtraImpute: a novel machine learning method for missing data imputation
by: Alabadla, Mustafa, et al.
Published: (2022)

Missing value estimation methods for data in linear functional relationship model
by: Adilah Abdul Ghapor,, et al.
Published: (2017)

Trust score measurement method for web donor selection and imputation of missing values
by: Jaya, M. Izham, et al.
Published: (2021)

A comparison of various imputation methods for missing values in air quality data
by: Nuryazmin Ahmat Zainuri,, et al.
Published: (2015)

Robust regression imputation for analyzing missing data
by: Rana, Md. Sohel, et al.
Published: (2012)

Statistical Modelling For Forecasting Pm10 Concentrations In Peninsular Malaysia
by: Ng, Kar Yong
Published: (2017)

Bivariate extreme value with application to PM10 concentration analysis
by: Mohd Amin, Nor Azrita, et al.
Published: (2014)

Extreme value theory for modeling and prediction of high PM10 concentration in Johor
by: Mohd Amin, Nor Azrita, et al.
Published: (2013)

Intelligent imputation method for mix data-type missing values to improve data quality
by: Alabadla, Mustafa R. A.
Published: (2024)

Missing variability in meta-analysis : is imputing always good?
by: Nik Idris, Nik Ruzni, et al.
Published: (2006)

Performance of selected imputation techniques for missing variances in meta-analysis
by: Nik Idris, Nik Ruzni, et al.
Published: (2012)

Performance of selected imputation techniques for missing variances in meta-analysis
by: Nik Idris, Nik Ruzni, et al.
Published: (2013)

Cold deck missing value imputation with a trust-based selection method of multiple web donors
by: Mohd Jaya, Mohd Izham
Published: (2018)

Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data
by: Tian, Ying
Published: (2024)

A systematic review of recurrent neural network adoption in missing data imputation
by: Nur Aqilah, Fadzil Akbar, et al.
Published: (2025)

Bayesian extreme for modeling high PM10 concentration in Johor
by: Mohd Amin, Nor Azrita, et al.
Published: (2015)

Probabilistic And Distribution Modelling For Predicting Pm10 Concentration In Malaysia
by: Hamid, Hazrul Abdul
Published: (2013)

Missing Value Imputation Improves Mortality Risk Prediction Following Cardiac Surgery: An Investigation of an Australian Patient Cohort
by: Karim, M., et al.
Published: (2015)

Determination of the best single imputation algorithm for missing rainfall data treatment
by: Gamil Abdulraqeb Abdullah Saeed,, et al.
Published: (2016)

Estimation of Missing Rainfall Data Using Spatial Interpolation and Imputation Methods
by: Roslinazairimah, Zakaria, et al.
Published: (2015)

Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment
by: Saeed, Gamil Abdulraqeb Abdullah, et al.
Published: (2016)

Robust Random Regression Imputation method for missing data in the presence of outliers
by: John, Ahamefule Happy
Published: (2013)

Diurval Variation Of PM10 And Carbon Monoxide Concentrations In Penang
by: Abd. Manaff, Liana Syafinaz
Published: (2005)

The effects of imputing the missing standard deviations on the standard error of meta analysis estimates
by: Nik Idris, Nik Ruzni, et al.
Published: (2009)

A case study on the effect of imputing the missing variability measures in meta analysis
by: Nik Idris, Nik Ruzni
Published: (2007)

Prediction Of Pm10 Concentrations Using Extreme Value Distributions (Evd) Classical And Bayesian Approaches
by: Ahmat, Hasfazilah
Published: (2016)

Modeling And Prediction Of Pm10 Concentration During High Particulate Events In Malaysia
by: Yusof, Noor Faizah Fitri Bt Md
Published: (2009)