Results 41 to 50 of about 313,820 (280)

Resampling Methods with Imputed Data

, 2023
Resampling techniques have become increasingly popular for estimation of uncertainty in data collected via surveys. Survey data are also frequently subject to missing data which are often imputed. This note addresses the issue of using resampling methods such as a jackknife or bootstrap in conjunction with imputations that have be sampled ...
Robbins, Michael W., Burgette, Lane, Bauhoff, Sebastian   +2 more
openaire   +2 more sources

A Pattern-Recognition-Based Ensemble Data Imputation Framework for Sensors from Building Energy Systems

Sensors, 2020
Building operation data are important for monitoring, analysis, modeling, and control of building energy systems. However, missing data is one of the major data quality issues, making data imputation techniques become increasingly important.
Liang Zhang
doaj   +1 more source

MissForest - nonparametric missing value imputation for mixed-type data

, 2011
Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set.
D. J. Stekhoven, Harley, Kurgan, Latal, LITTLE, Oba, P. Buhlmann, Smit, Troyanskaya, van Buuren, Wille, Wu   +11 more
core   +1 more source

Imputation of truncated p-values for meta-analysis methods and its genomic application

, 2014
Microarray analysis to monitor expression activities in thousands of genes simultaneously has become routine in biomedical research during the past decade.
Ding, Ying, Lariviere, William R., Mogil, Jeffrey S., Sibille, Etienne, Tang, Shaowu, Tseng, George C.   +5 more
core   +1 more source

Imputation methods for filling missing data in urban air pollution data for Malaysia [PDF]

Urbanism. Arhitectura. Constructii, 2018
The air quality measurement data obtained from the continuous ambient air quality monitoring (CAAQM) station usually contained missing data. The missing observations of the data usually occurred due to machine failure, routine maintenance and human error.
Nur Afiqah Zakaria, Norazian Mohamed Noor   +1 more
doaj  

Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds [PDF]

, 2013
Background The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP.
AJ Chamberlain, APW de Roos, BJ Hayes, BJ Hayes, BJ Hayes, BL Browning, C Dimauro, C Hagger, Corrado Dimauro, D Boichard, D Segelke, DP Berry, G Li, G Moser, Gabriele Marras, GCB Schopen, Giustino Gaspa, H Abdi, HA Mulder, HD Daetwyler, I Medugorac, J Chen, JE Pryce, JM Hickey, K Kizilkaya, KA Weigel, KA Weigel, Massimo Cellesi, Nicolò PP Macciotta, P Ajmone-Marsan, P Scheet, Paolo Ajmone-Marsan, PM VanRaden, R Dassonneville, R Dassonneville, Roberto Steri, T Druet, T Druet, TH Meuwissen, Z Zhang   +39 more
core   +3 more sources

Comparison of Performance of Data Imputation Methods for Numeric Dataset

Applied Artificial Intelligence, 2019
Missing data is common problem faced by researchers and data scientists. Therefore, it is required to handle them appropriately in order to get better and accurate results of data analysis.
Anil Jadhav, Dhanya Pramod, Krishnan Ramanathan   +2 more
doaj   +1 more source

Multiple Imputation: Theory and Method

International Statistical Review, 2003
SummaryIn this review paper, we discuss the theoretical background of multiple imputation, describe how to build an imputation model and how to create proper imputations. We also present the rules for making repeated imputation inferences. Three widely used multiple imputation methods, the propensity score method, the predictive model method and the ...
openaire   +3 more sources

Imputation methods for doubly censored HIV data [PDF]

Journal of Statistical Computation and Simulation, 2009
In medical research, it is common to have doubly censored survival data: origin time and event time are both subject to censoring. In this paper, we review simple and probability-based methods that are used to impute interval censored origin time and compare the performance of these methods through extensive simulations in the one-sample problem, two ...
Wei, Zhang, Ying, Zhang, Kathryn, Chaloner, Jack T, Stapleton   +3 more
openaire   +2 more sources

GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies. [PDF]

PLoS Computational Biology, 2018
Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses ...
Runmin Wei, Jingye Wang, Erik Jia, Tianlu Chen, Yan Ni, Wei Jia   +5 more
doaj   +1 more source