Quantum Circuit for Imputation of Missing Data by Claudio Sanavio, Simone Tibaldi, Edoardo Tignone, Elisa Ercolessi

Subjects: “…Imputation missing data…”
Get full text

A Prediction Method for the RUL of Equipment for Missing Data by Chen Wenbai, Liu Chang, Chen Weizhao, Liu Huixiang, Chen Qili, Wu Peiliang

“…First, a binary matrix is used to adjust the proportion of “0” to simulate the number of missing data in the engineering environment. Then, the GAIN model is used to impute the missing data and approximate the true sample distribution. …”
Get full text

Advances in Biomedical Missing Data Imputation: A Survey by Miriam Barrabes, Maria Perera, Victor Novelle Moriano, Xavier Giro-I-Nieto, Daniel Mas Montserrat, Alexander G. Ioannidis

“…This survey paper provides a comprehensive overview of the extensive literature on missing data imputation techniques, with a specific focus on applications in genomics, single-cell RNA sequencing, health records, and medical imaging. …”
Get full text

Look-alike modelling in violence-related research: A missing data approach. by Estela Capelas Barbosa, Niels Blom, Annie Bunce

“…Methodologically, we approached data integration as a missing data problem to create a synthetic combined dataset. …”
Get full text

A generative model for evaluating missing data methods in large epidemiological cohorts by Lav Radosavljević, Stephen M. Smith, Thomas E. Nichols

Subjects: Get full text

UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data by Karen Uribe-Murcia, Yuriy S. Shmaliy, Jose A. Andrade-Lucio

“…The UFIR filter is developed for vehicle tracking in discrete-time state-space over wireless sensor networks (WSNs) with time-stamped data discretely delayed on k-step-lags and missing data. The state-space model is represented in a way such that the UFIR filter, KF, and H∞ filter can be used universally. …”
Get full text

Study on Missing Data Filling Algorithm of Nuclear Power Plant Operation Parameters by Tianshu Wang, Ren Yu, Qiao Peng

“…Firstly, to locate the missing data accurately the detecting algorithm for missing data of the NPP operation parameters based on wavelet analysis. …”
Get full text

Enhancing imputation accuracy for catch-all missing data mechanisms with DFBETAS and leverage by Fares Qeadan, William A. Barbeau

Subjects: “…Missing data…”
Get full text

Implementation of Missing Data Imputation Schemes in Face Recognition Algorithm under Partial Occlusion by Justice Kwame Appati, Kofi Sarpong Adu-Manu, Ebenezer Owusu

“…Further experimentation shows that IA is an ideal missing data imputation scheme that works best with the SVD/PCA facial recognition algorithm.…”
Get full text

Addressing Missing Data in Slope Displacement Monitoring: Comparative Analysis of Advanced Imputation Methods by Seungjoo Lee, Yongjin Kim, Bongjun Ji, Yongseong Kim

“…However, continuous data collection is often disrupted by environmental factors, sensor malfunctions, and communication issues, leading to missing data that can compromise analysis accuracy and reliability. …”
Get full text

Fractional Gradient Descent-Based Auxiliary Model Algorithm for FIR Models with Missing Data by Jia Tang

“…This study proposes a fractional gradient descent (FGD) algorithm for FIR models with missing data. By using the auxiliary model method, the missing data can be obtained. …”
Get full text

The Performance of Multiple Imputation in Social Surveys with Missing Data from Planned Missingness and Item Nonresponse by Julian B. Axenfeld, Christian Bruch, Christof Wolf, Annelies G. Blom

Subjects: Get full text

Overcoming Missing Data: Accurately Predicting Cardiovascular Risk in Type 2 Diabetes, A Systematic Review by Wenhui Ren, Keyu Fan, Zheng Liu, Yanqiu Wu, Haiyan An, Huixin Liu

“…Most articles reported missing data in the development (n = 40/51) and external validation (n = 12/16) stages. …”
Get full text

Working with Missing Data: Imputation of Nonresponse Items in Categorical Survey Data with a Non-Monotone Missing Pattern by Machelle D. Wilson, Kerstin Lueck

“…The imputation of missing data is often a crucial step in the analysis of survey data. …”
Get full text

What you don’t know can hurt you: a statistical commentary on missing data in trauma research by Molly P Jarman, James P Byrne

Get full text

A traffic prediction method for missing data scenarios: graph convolutional recurrent ordinary differential equation network by Ming Jiang, Zhiwei Liu, Yan Xu

Subjects: Get full text

Unsupervised data imputation with multiple importance sampling variational autoencoders by Shenfen Kuang, Yewen Huang, Jie Song

Subjects: “…Missing data…”
Get full text

Optimal adjustment of deep neural network parameters in estimating lost vital sign data in body wireless sensor networks by Aboulfazl Ebrahimi, Mahboubeh Shamsi, Morteza Mohajjel

Subjects: Get full text

How much missing data is too much to impute for longitudinal health indicators?... by K. P. Junaid, Tanvi Kiran, Madhu Gupta, Kamal Kishore, Sujata Siwatch

“…Abstract Background The multiple imputation by chained equations (MICE) is a widely used approach for handling missing data. However, its robustness, especially for high missing proportions in health indicators, is under-researched. …”
Get full text

Spatiotemporal variation in size-dependent growth rates in small isolated populations of Arctic charr (Salvelinus alpinus) by Elizabeth A. Mittell, Camille A. Leblanc, Bjarni K. Kristjánsson, Moira M. Ferguson, Katja Räsänen, Michael B. Morrissey

Subjects: Get full text