Results 61 to 70 of about 16,362,739 (323)
Nonconvex
IEEE Access, 2018 Recovering missing values from incomplete traffic sensor data is an important task for intelligent transportation system because most algorithms require data with complete entries as input.
Xiaobo Chen +3 more
doaj +1 more source
Development Of Adaptive Moving Two–sided Exponential Smoothing Method For Restoring And Forecasting Of TIME Series [PDF]
, 2017 Two algorithms for restoring of missing values of time series with using of adaptive moving two-sided exponential smoothing method with different initial conditions are developed in the article.
Bratus, O. (Olena)
core +2 more sources
Handling missing values in trait data
Global Ecology and Biogeography, 2020 Aim Trait data are widely used in ecological and evolutionary phylogenetic comparative studies, but often values are not available for all species of interest. Researchers traditionally have excluded species without data from analyses, but estimation of
T. F. Johnson +3 more
semanticscholar +1 more source
Treatment Decision‐Making Roles and Preferences Among Adolescents and Young Adults With Cancer
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Decision‐making (DM) dynamics between adolescents and young adults (AYAs) with cancer, parents, and oncologists remain underexplored in diverse populations. We examined cancer treatment DM preferences among an ethnically and socioeconomically diverse group of AYAs and their parents.
Amanda M. Gutierrez +14 more
wiley +1 more source
Swiss Journal of Economics and Statistics, 2016 Summary We present an integration based procedure for predicting the distribution f of an indicator of interest in situations where, in addition to the sample data, one has access to covariates that are available for the entire population.
Jing Dai +2 more
doaj +1 more source
Comment on "Spatio-temporal filling of missing points in geophysical data sets" by D. Kondrashov and M. Ghil, Nonlin. Processes Geophys., 13, 151–159, 2006 [PDF]
, 2007 Kondrashov and Ghil (2006) (KG hereafter) describe a method for imputing missing values in incomplete datasets that can exploit both spatial and temporal covariability to estimate missing values from available values.
Schneider, T.
core +1 more source
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values [PDF]
AAAI Conference on Artificial Intelligence, 2019 Multivariate time series (MTS) forecasting is widely used in various domains, such as meteorology and traffic. Due to limitations on data collection, transmission, and storage, real-world MTS data usually contains missing values, making it infeasible to ...
Xianfeng Tang +5 more
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Parents of children treated for acute lymphoblastic leukemia (ALL) often experience significant caregiver burden and disruption to their well‐being. While parent quality of life (QoL) during treatment is well characterized, little is known about outcomes during early survivorship.
Sara Dal Pra +3 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Cognitive and psychological difficulties could negatively interfere with treatment adherence and quality of life before and after hematopoietic stem cell transplant (HSCT). Methods to mitigate these changes may have positive effects on treatment success.
Kristen L. Votruba +11 more
wiley +1 more source
Software for handling and replacement of missing data
GMS Medizinische Informatik, Biometrie und Epidemiologie, 2009 In medical research missing values often arise in the course of a data analysis. This fact constitutes a problem for different reasons, so e.g. standard methods for analyzing data lead to biased estimates and a loss of statistical power due to missing ...
Mayer, Benjamin +2 more
doaj