Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
What Affects Parents’ Choice Of Milk? An Application Of Bayesian Model Averaging, Yingzhe Cheng
What Affects Parents’ Choice Of Milk? An Application Of Bayesian Model Averaging, Yingzhe Cheng
Mathematics & Statistics ETDs
This study identifies the factors that influence parents’ choice of milk for their children, using data from a unique survey administered in 2013 in Hunan province, China. In this survey, we identified two brands of milk, which differ in their prices and safety claims by the producer. Data were collected on parents’ choice of milk between the two brands, demographics, attitude towards food safety and behaviors related to food. Stepwise model selection and Bayesian model averaging (BMA) are used to search for influential factors. The two approaches consistently select the same factors suggested by an economic theoretical model, including price …
Mechanistic Plug-And-Play Models For Understanding The Impact Of Control And Climate On Seasonal Dengue Dynamics In Iquitos, Peru, Nathan Levick
Mechanistic Plug-And-Play Models For Understanding The Impact Of Control And Climate On Seasonal Dengue Dynamics In Iquitos, Peru, Nathan Levick
Mathematics & Statistics ETDs
Dengue virus is a mosquito-borne multi-serotype disease whose dynamics are not precisely understood despite half of the world’s human population being at risk of infection. A recent dataset of dengue case reports from an isolated Amazonian city— Iquitos, Peru—provides a unique opportunity to assess dengue dynamics in a simpli- fied setting. Ten years of clinical surveillance data reveal a specific pattern: two novel serotypes, in turn, invaded and exclusively dominated incidence over several seasonal cycles, despite limited intra-annual variation in climate conditions. Together with mechanistic mathematical models, these data can provide an improved understand- ing of the nonlinear interactions between …
Data Driven Sample Generator Model With Application To Classification, Alvaro Emilio Ulloa Cerna
Data Driven Sample Generator Model With Application To Classification, Alvaro Emilio Ulloa Cerna
Mathematics & Statistics ETDs
Despite the rapidly growing interest, progress in the study of relations between physiological abnormalities and mental disorders is hampered by complexity of the human brain and high costs of data collection. The complexity can be captured by machine learning approaches, but they still may require significant amounts of data. In this thesis, we seek to mitigate the latter challenge by developing a data driven sample generator model for the generation of synthetic realistic training data. Our method greatly improves generalization in classification of schizophrenia patients and healthy controls from their structural magnetic resonance images. A feed forward neural network trained …