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pro vyhledávání: '"Kuschinski, Nicolás"'
Probability density estimation is a central task in statistics. Copula-based models provide a great deal of flexibility in modelling multivariate distributions, allowing for the specifications of models for the marginal distributions separately from
Externí odkaz:
http://arxiv.org/abs/2405.04475
A common test for the diagnosis of type 2 diabetes is the Oral Glucose Tolerance Test (OGTT). Recent developments in the study of OGTT tests have framed it as a Bayesian inverse problem. These data analysis advances promise great improvements in the
Externí odkaz:
http://arxiv.org/abs/2303.06441
Autor:
Kuschinski, Nicolás, Jara, Alejandro
Copula-based models provide a great deal of flexibility in modelling multivariate distributions, allowing for the specifications of models for the marginal distributions separately from the dependence structure (copula) that links them to form a join
Externí odkaz:
http://arxiv.org/abs/2109.03768
In linear models it is common to have situations where several regression coefficients are zero. In these situations a common tool to perform regression is a variable selection operator. One of the most common such operators is the LASSO operator, wh
Externí odkaz:
http://arxiv.org/abs/1904.05828
OGTT is a common test, frequently used to diagnose insulin resistance or diabetes, in which a patient's blood sugar is measured at various times over the course of a few hours. Recent developments in the study of OGTT results have framed it as an inv
Externí odkaz:
http://arxiv.org/abs/1903.11697
One common way to test for diabetes is the Oral Glucose Tolerance Test or OGTT. Most common methods for the analysis of the data on this test are wasteful of much of the information contained therein. We propose to model blood glucose during an OGTT
Externí odkaz:
http://arxiv.org/abs/1601.04753