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pro vyhledávání: '"62j05"'
In this work, we study the well-posedness of certain sparse regularized linear regression problems, i.e., the existence, uniqueness and continuity of the solution map with respect to the data. We focus on regularization functions that are convex piec
Externí odkaz:
http://arxiv.org/abs/2409.03461
Handling high-dimensional datasets presents substantial computational challenges, particularly when the number of features far exceeds the number of observations and when features are highly correlated. A modern approach to mitigate these issues is f
Externí odkaz:
http://arxiv.org/abs/2408.13000
Autor:
Knaeble, Brian, Kummerfeld, Erich
We consider the following comparative effectiveness scenario. There are two treatments for a particular medical condition: a randomized experiment has demonstrated mediocre effectiveness for the first treatment, while a non-randomized study of the se
Externí odkaz:
http://arxiv.org/abs/2408.12098
It can be difficult to interpret a coefficient of an uncertain model. A slope coefficient of a regression model may change as covariates are added or removed from the model. In the context of high-dimensional data, there are too many model extensions
Externí odkaz:
http://arxiv.org/abs/2408.09634
This article introduces operator on operator regression in quantum probability. Here in the regression model, the response and the independent variables are certain operator valued observables, and they are linearly associated with unknown scalar coe
Externí odkaz:
http://arxiv.org/abs/2408.00289
Autor:
Kurata, Sumito, Hirose, Kei
In the last two decades, sparse regularization methods such as the LASSO have been applied in various fields. Most of the regularization methods have one or more regularization parameters, and to select the value of the regularization parameter is es
Externí odkaz:
http://arxiv.org/abs/2407.16116
Autor:
Pu, Zhibin, Ge, Shufei
Imaging genetics aims to uncover the hidden relationship between imaging quantitative traits (QTs) and genetic markers (e.g. single nucleotide polymorphism (SNP)), and brings valuable insights into the pathogenesis of complex diseases, such as cancer
Externí odkaz:
http://arxiv.org/abs/2407.04530
Autor:
Zhang, Tonglin
A new method called the aggregated sure independence screening is proposed for the computational challenges in variable selection of interactions when the number of explanatory variables is much higher than the number of observations (i.e., $p\gg n$)
Externí odkaz:
http://arxiv.org/abs/2407.03558
When the regressors of a econometric linear model are nonorthogonal, it is well known that their estimation by ordinary least squares can present various problems that discourage the use of this model. The ridge regression is the most commonly used a
Externí odkaz:
http://arxiv.org/abs/2407.02583
The paper analyzes how the enlarging of the sample affects to the mitigation of collinearity concluding that it may mitigate the consequences of collinearity related to statistical analysis but not necessarily the numerical instability. The problem t
Externí odkaz:
http://arxiv.org/abs/2407.01172