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Physical Sciences and Mathematics Commons™
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- Cannabis use (1)
- Confirmatory Tetrad Analysis (1)
- Displacement Vector Field (1)
- GWAS (1)
- Low-rank Approximation (1)
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- Lung Respiratory Motion Model (1)
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- Model complexity (1)
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- Population Value Decomposition (1)
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- Structural Equation Modeling (1)
- Tensor Decomposition (1)
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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Stochastic Averaging For Multiple Cooperative And Antagonistic Molecular Motors, Joe Klobusicky
Stochastic Averaging For Multiple Cooperative And Antagonistic Molecular Motors, Joe Klobusicky
Biology and Medicine Through Mathematics Conference
No abstract provided.
Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares
Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares
Biology and Medicine Through Mathematics Conference
No abstract provided.
Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang
Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang
Theses and Dissertations
Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation.
With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a …
Examining The Confirmatory Tetrad Analysis (Cta) As A Solution Of The Inadequacy Of Traditional Structural Equation Modeling (Sem) Fit Indices, Hangcheng Liu
Theses and Dissertations
Structural Equation Modeling (SEM) is a framework of statistical methods that allows us to represent complex relationships between variables. SEM is widely used in economics, genetics and the behavioral sciences (e.g. psychology, psychobiology, sociology and medicine). Model complexity is defined as a model’s ability to fit different data patterns and it plays an important role in model selection when applying SEM. As in linear regression, the number of free model parameters is typically used in traditional SEM model fit indices as a measure of the model complexity. However, only using number of free model parameters to indicate SEM model complexity …
Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry
Penalized Mixed-Effects Ordinal Response Models For High-Dimensional Genomic Data In Twins And Families, Amanda E. Gentry
Theses and Dissertations
The Brisbane Longitudinal Twin Study (BLTS) was being conducted in Australia and was funded by the US National Institute on Drug Abuse (NIDA). Adolescent twins were sampled as a part of this study and surveyed about their substance use as part of the Pathways to Cannabis Use, Abuse and Dependence project. The methods developed in this dissertation were designed for the purpose of analyzing a subset of the Pathways data that includes demographics, cannabis use metrics, personality measures, and imputed genotypes (SNPs) for 493 complete twin pairs (986 subjects.) The primary goal was to determine what combination of SNPs and …